{"id":33453,"date":"2026-04-27T04:31:35","date_gmt":"2026-04-26T23:01:35","guid":{"rendered":"https:\/\/icert.org.in\/?p=33453"},"modified":"2026-04-27T05:42:01","modified_gmt":"2026-04-27T00:12:01","slug":"application-of-fuzzy-based-data-mining-techniques-in-breast-cancer-diagnosis-and-prognosis","status":"publish","type":"post","link":"https:\/\/icert.org.in\/index.php\/2026\/04\/27\/application-of-fuzzy-based-data-mining-techniques-in-breast-cancer-diagnosis-and-prognosis\/","title":{"rendered":"Application Of Fuzzy-Based Data Mining Techniques in Breast Cancer Diagnosis and Prognosis"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"33453\" class=\"elementor elementor-33453\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-20f57a4 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"20f57a4\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-fe227a0\" data-id=\"fe227a0\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-5610a4f elementor-widget elementor-widget-heading\" data-id=\"5610a4f\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h1 class=\"elementor-heading-title elementor-size-default\">Shodh Sari-An International Multidisciplinary Journal<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-52c975d elementor-widget elementor-widget-heading\" data-id=\"52c975d\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Vol-05, Issue-02(Apr - Jun 2026)<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8a02dcf elementor-widget elementor-widget-heading\" data-id=\"8a02dcf\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h5 class=\"elementor-heading-title elementor-size-default\">An International scholarly\/ academic journal, peer-reviewed\/ refereed journal, ISSN : 2959-1376<\/h5>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-e3fd92c elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"e3fd92c\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-19c060d\" data-id=\"19c060d\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-42f4741 elementor-widget elementor-widget-heading\" data-id=\"42f4741\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Application Of Fuzzy-Based Data Mining Techniques in Breast Cancer Diagnosis and Prognosis<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8804743 elementor-widget elementor-widget-text-editor\" data-id=\"8804743\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p dir=\"ltr\" style=\"line-height: 1.8; margin-top: 0pt; margin-bottom: 8pt; text-align: center;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: #ffffff; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Bhatnagar, Parul<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: #ffffff; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"><span style=\"font-size: 0.6em; vertical-align: super;\">1<\/span><\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: #ffffff; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> and Kumar, Bhupendra<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: #ffffff; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"><span style=\"font-size: 0.6em; vertical-align: super;\">2<\/span><\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.2; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: #ffffff; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"><span style=\"font-size: 0.6em; vertical-align: super;\">1<\/span><\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: #ffffff; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Research Scholar, School of Computer Science &amp; Applications, IIMT University Meerut, Uttar Pradesh, India<\/span><\/p><p style=\"text-align: center;\"><span style=\"font-size: 12pt; font-family: Arial, sans-serif; color: #000000; font-variant: normal; vertical-align: baseline; white-space: pre-wrap;\"><span style=\"font-size: 0.6em; vertical-align: super;\">2<\/span><\/span><span style=\"font-size: 12pt; font-family: Arial, sans-serif; color: #000000; font-variant: normal; vertical-align: baseline; white-space: pre-wrap;\">Professor, School of Computer Science &amp; Applications, IIMT University Meerut, Uttar Pradesh, India<\/span><\/p><p style=\"text-align: center;\"><a href=\"https:\/\/orcid.org\/0000-0001-9281-3655\" target=\"_blank\" rel=\"noopener\">ORCiD:0000-0001-9281-3655<\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-ce1c0a4 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"ce1c0a4\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-ae11d16\" data-id=\"ae11d16\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-3d0b84b elementor-widget__width-inherit elementor-widget elementor-widget-elementskit-simple-tab\" data-id=\"3d0b84b\" data-element_type=\"widget\" data-widget_type=\"elementskit-simple-tab.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"ekit-wid-con\" >        <div class=\"elementkit-tab-wraper vertical  elementskit-fitcontent-tab \">\n            <ul class=\"nav nav-tabs elementkit-tab-nav \">\n                                    <li class=\"elementkit-nav-item elementor-repeater-item-ca158ed\">\n                        <a class=\"elementkit-nav-link  active show left-pos\" id=\"content-ca158ed69f1a56767f7f-tab\" data-ekit-handler-id=\"abstract\" data-ekit-toggle=\"tab\" data-target=\"#content-ca158ed69f1a56767f7f\" href=\"#Content-ca158ed69f1a56767f7f\"\n                            data-ekit-toggle-trigger=\"click\"\n                            aria-describedby=\"Content-ca158ed69f1a56767f7f\">\n                            <span class=\"far fa-file-alt elementskit-tab-icon\"><\/span>                            <span class=\"elementskit-tab-title\"> Abstract<\/span>\n                        <\/a>\n                    <\/li>\n                                        <li class=\"elementkit-nav-item elementor-repeater-item-62e3348\">\n                        <a class=\"elementkit-nav-link  left-pos\" id=\"content-62e334869f1a56767f7f-tab\" data-ekit-handler-id=\"about-author\" data-ekit-toggle=\"tab\" data-target=\"#content-62e334869f1a56767f7f\" href=\"#Content-62e334869f1a56767f7f\"\n                            data-ekit-toggle-trigger=\"click\"\n                            aria-describedby=\"Content-62e334869f1a56767f7f\">\n                            <span class=\"far fa-user elementskit-tab-icon\"><\/span>                            <span class=\"elementskit-tab-title\"> About Author<\/span>\n                        <\/a>\n                    <\/li>\n                                        <li class=\"elementkit-nav-item elementor-repeater-item-e351830\">\n                        <a class=\"elementkit-nav-link  left-pos\" id=\"content-e35183069f1a56767f7f-tab\" data-ekit-handler-id=\"impact-statement\" data-ekit-toggle=\"tab\" data-target=\"#content-e35183069f1a56767f7f\" href=\"#Content-e35183069f1a56767f7f\"\n                            data-ekit-toggle-trigger=\"click\"\n                            aria-describedby=\"Content-e35183069f1a56767f7f\">\n                            <span class=\"fas fa-file-import elementskit-tab-icon\"><\/span>                            <span class=\"elementskit-tab-title\"> Impact Statement<\/span>\n                        <\/a>\n                    <\/li>\n                                        <li class=\"elementkit-nav-item elementor-repeater-item-bb8dae5\">\n                        <a class=\"elementkit-nav-link  left-pos\" id=\"content-bb8dae569f1a56767f7f-tab\" data-ekit-handler-id=\"cite-this-article\" data-ekit-toggle=\"tab\" data-target=\"#content-bb8dae569f1a56767f7f\" href=\"#Content-bb8dae569f1a56767f7f\"\n                            data-ekit-toggle-trigger=\"click\"\n                            aria-describedby=\"Content-bb8dae569f1a56767f7f\">\n                            <span class=\"far fa-address-card elementskit-tab-icon\"><\/span>                            <span class=\"elementskit-tab-title\"> Cite this Article<\/span>\n                        <\/a>\n                    <\/li>\n                                <\/ul>\n\n            <div class=\"tab-content elementkit-tab-content\">\n                                    <div class=\"tab-pane elementkit-tab-pane elementor-repeater-item-ca158ed  active show\" id=\"content-ca158ed69f1a56767f7f\" role=\"tabpanel\"\n                         aria-labelledby=\"content-ca158ed69f1a56767f7f-tab\">\n                        <div class=\"animated fadeIn\">\n                            <p dir=\"ltr\" style=\"line-height: 1.2; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Abstract<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; border-bottom: solid #000000 1.5pt; margin-top: 0pt; margin-bottom: 8pt; padding: 0pt 0pt 1pt 0pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Early detection and proper prognosis are important in the treatment of breast cancer as it is one of the major causes of death in women across the world. Traditional diagnostic and predictive models typically do not cope with uncertainty and imprecision of clinical data, which leads to the decrease in reliability in practice. This paper seeks to explore the use of fuzzy-based data mining methods to improve both the prognosis and diagnosis of breast cancer. The research design is quantitative predictive research design based on 250 simulated patient records comprised of tumor characteristics, uniformity of cells, mitotic rate and other diagnostic markers. Preprocessing of key clinical variables is done and encoded into linguistic terms then put through a feature selection process using correlation analysis and fuzzy entropy measures to maximize model efficiency. Development of a fuzzy-based classifier is achieved by fuzzification, rule generation, inference, and defuzzification, which allows fine-tuning of disease presence (Benign\/Malignant) and prognosis risk (Low, Moderate, High). The evaluation of performance is performed on the basis of 10-fold cross-validation, and the measures of accuracy, sensitivity, specificity, precision, and F1-score are compared to the traditional machine learning models: Artificial Neural Networks, Support Vector Machines, and Decision Trees. These findings indicate that the fuzzy-based classifier performs better than traditional models and the accuracy of the fuzzy-based classifier is 94 and 92 in diagnosis and prognosis respectively with high sensitivity, specificity, precision, and F1-scores in both tasks. The confusion analysis also proves the strength of the model as there are few misclassifications and solid predictions in all the risk categories. The results suggest that fuzzy-based methods are useful to deal with overlapping and imprecise clinical features, to provide interpretable and actionable clinical decision-making. Lastly, the study reaffirms the fuzzy-based data mining as a robust, flexible and clinically feasible model of breast cancer diagnosis and prognosis, which allows one to diagnose a patient early, assess the risks properly and treat him\/her individually. This approach can be extended to future studies using large real <\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">patient datasets and incorporating ensemble learning or real-time monitoring in order to realize more predictive capability and clinical utility.<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; border-bottom: solid #000000 1.5pt; margin-top: 0pt; margin-bottom: 8pt; padding: 0pt 0pt 1pt 0pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Keywords:<\/span> <span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Breast Cancer, Diagnosis, Prognosis, Fuzzy Logic, Data Mining, Clinical Data, Feature Selection, Predictive Modeling<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">.<\/span><\/p>                        <\/div>\n                    <\/div>\n                                    <div class=\"tab-pane elementkit-tab-pane elementor-repeater-item-62e3348 \" id=\"content-62e334869f1a56767f7f\" role=\"tabpanel\"\n                         aria-labelledby=\"content-62e334869f1a56767f7f-tab\">\n                        <div class=\"animated fadeIn\">\n                            <p dir=\"ltr\" style=\"line-height: 1.8; margin-top: 0pt; margin-bottom: 8pt; text-align: center;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">About the Authors<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Parul Bhatnagar is a Research Scholar at the School of Computer Science &amp; Applications, IIMT University, Meerut. Her research interests include healthcare data mining, artificial intelligence, and the application of soft computing techniques to solve complex medical diagnostic problems.<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Dr. Bhupendra Kumar is a Professor at the School of Computer Science &amp; Applications, IIMT University, Meerut. An expert in data analytics and intelligent systems, he has supervised numerous research projects focused on leveraging technology to enhance socio-economic and medical outcomes.<\/span><\/p>                        <\/div>\n                    <\/div>\n                                    <div class=\"tab-pane elementkit-tab-pane elementor-repeater-item-e351830 \" id=\"content-e35183069f1a56767f7f\" role=\"tabpanel\"\n                         aria-labelledby=\"content-e35183069f1a56767f7f-tab\">\n                        <div class=\"animated fadeIn\">\n                            <p dir=\"ltr\" style=\"line-height: 1.8; margin-top: 0pt; margin-bottom: 8pt; text-align: center;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Impact Statement<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">This research significantly advances the field of medical informatics by addressing the inherent uncertainty and imprecision in clinical breast cancer data. By integrating fuzzy logic with data mining, the study provides a more nuanced diagnostic tool that mimics human reasoning, leading to higher accuracy in both early detection and long-term prognosis. The practical impact lies in its potential to serve as a reliable Decision Support System (DSS) for oncologists, reducing false negatives and enabling personalized treatment pathways. Ultimately, these computational improvements contribute to better patient survival rates and optimized healthcare resource management.<\/span><\/p>                        <\/div>\n                    <\/div>\n                                    <div class=\"tab-pane elementkit-tab-pane elementor-repeater-item-bb8dae5 \" id=\"content-bb8dae569f1a56767f7f\" role=\"tabpanel\"\n                         aria-labelledby=\"content-bb8dae569f1a56767f7f-tab\">\n                        <div class=\"animated fadeIn\">\n                            <p dir=\"ltr\" style=\"line-height: 1.8; margin-top: 0pt; margin-bottom: 8pt; text-align: center;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Cite This Article<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">APA Style (7th Edition): Bhatnagar, P., &amp; Kumar, B. (2026). Application of fuzzy-based data mining techniques in breast cancer diagnosis and prognosis. <\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Shodh Sari-An International Multidisciplinary Journal, 5<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(2), 543\u2013560. https:\/\/doi.org\/10.59231\/SARI7939<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Chicago Style (17th Edition): Bhatnagar, Parul, and Bhupendra Kumar. &#8220;Application of Fuzzy-Based Data Mining Techniques in Breast Cancer Diagnosis and Prognosis.&#8221; <\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Shodh Sari-An International Multidisciplinary Journal<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> 5, no. 2 (2026): 543\u2013560. https:\/\/doi.org\/10.59231\/SARI7939.<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">MLA Style (9th Edition): Bhatnagar, Parul, and Bhupendra Kumar. &#8220;Application of Fuzzy-Based Data Mining Techniques in Breast Cancer Diagnosis and Prognosis.&#8221; <\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Shodh Sari-An International Multidisciplinary Journal<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, vol. 5, no. 2, 2026, pp. 543\u2013560, https:\/\/doi.org\/10.59231\/SARI7939.<\/span><\/p>                        <\/div>\n                    <\/div>\n                                \n            <\/div>\n                    <\/div>\n    <\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-1d53b9f elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"1d53b9f\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-20 elementor-top-column elementor-element elementor-element-a9ad766\" data-id=\"a9ad766\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-3d03e55 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class=\"elementor-column elementor-col-20 elementor-top-column elementor-element elementor-element-75781a2\" data-id=\"75781a2\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-37b0ea0 elementor-align-justify elementor-mobile-align-left elementor-widget-tablet__width-initial elementor-widget elementor-widget-button\" data-id=\"37b0ea0\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/archive.org\/download\/395.-application-of-fuzzy-based-data-mining-techniques-in-breast-cancer-diagnosis-and-prognosis\/395.%20Application%20Of%20Fuzzy-Based%20Data%20Mining%20Techniques%20In%20Breast%20Cancer%20Diagnosis%20And%20Prognosis.pdf\">\n\t\t\t\t\t\t<span 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class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-eb6543f elementor-widget-tablet__width-initial elementor-widget elementor-widget-shortcode\" data-id=\"eb6543f\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-shortcode\"><div class=\"sdm_download_count\"><span class=\"sdm_count_number\">8<\/span><span class=\"sdm_count_string\"> Downloads<\/span><\/div><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-4bfdcb2 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"4bfdcb2\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-b7a4ab4\" data-id=\"b7a4ab4\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-inner-section elementor-element elementor-element-e668ae6 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"e668ae6\" data-element_type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-inner-column elementor-element elementor-element-6e88547\" data-id=\"6e88547\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-8836a1f elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"8836a1f\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p dir=\"ltr\" style=\"line-height: 1.2; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">DOI: <\/span><a style=\"text-decoration: none;\" href=\"https:\/\/doi.org\/10.59231\/SARI7939\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #0563c1; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">https:\/\/doi.org\/10.59231\/SARI7939<\/span><\/a><\/p><p dir=\"ltr\" style=\"line-height: 1.2; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Subject: Computer Science \/ Healthcare Informatics<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.2; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Page No.: 543\u2013560<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-inner-column elementor-element elementor-element-673827a\" data-id=\"673827a\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-21d7739 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"21d7739\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p dir=\"ltr\" style=\"line-height: 1.2; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Received: Aug 29, 2025<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.2; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Accepted: Jan 03, 2026<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.2; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Published: Apr 24, 2026<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-aa0519d elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"aa0519d\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p dir=\"ltr\" style=\"line-height: 1.2; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Thematic Classification: Data Mining, Fuzzy Logic Systems, Medical Diagnosis, Computational Oncology, Predictive Analytics.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-7e219b9 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"7e219b9\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-35c95ef\" data-id=\"35c95ef\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-0095849 elementor-widget elementor-widget-heading\" data-id=\"0095849\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h6 class=\"elementor-heading-title elementor-size-default\">Introduction\n<\/h6>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7cffdaa elementor-widget elementor-widget-text-editor\" data-id=\"7cffdaa\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Breast cancer is one of the most common causes of cancer related deaths among women all over the world with the incidence of the disease continuously rising due to lifestyle change<\/span><a style=\"text-decoration: none;\" href=\"https:\/\/docs.google.com\/document\/d\/1U7WK73YUxDxH4fSh6h1Ki_ZOqUR5VIbFYXQ2uiT0jAM\/edit#bookmark=id.tcd1svwgamuu\"> <span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #0563c1; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(Roshani et al., 2015)<\/span><\/a><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, genetic abnormalities and environment<\/span><a style=\"text-decoration: none;\" href=\"https:\/\/docs.google.com\/document\/d\/1U7WK73YUxDxH4fSh6h1Ki_ZOqUR5VIbFYXQ2uiT0jAM\/edit#bookmark=id.uu08vsg0c8k\"> <span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #0563c1; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(Diz et al., 2016)<\/span><\/a><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">. In reducing the mortality rates and improving the quality of lives of patients, early and appropriate diagnosis is important and successful prognosis<\/span><a style=\"text-decoration: none;\" href=\"https:\/\/docs.google.com\/document\/d\/1U7WK73YUxDxH4fSh6h1Ki_ZOqUR5VIbFYXQ2uiT0jAM\/edit#bookmark=id.a5ylh9wggrmm\"> <span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #0563c1; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(Oskouei et al., 2017)<\/span><\/a><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">. The conventional diagnostic techniques of mammography, ultrasound, biopsy and histopathology give inimitable loads of clinical and imaging data<\/span><a style=\"text-decoration: none;\" href=\"https:\/\/docs.google.com\/document\/d\/1U7WK73YUxDxH4fSh6h1Ki_ZOqUR5VIbFYXQ2uiT0jAM\/edit#bookmark=id.lfnzi2hhwk0d\"> <span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #0563c1; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(Rajendran et al., 2019)<\/span><\/a><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">. However, these methods are normally criticized by interpretation variability, inexactness of measures and overlapping characteristics of benign and malignant tumors<\/span><a style=\"text-decoration: none;\" href=\"https:\/\/docs.google.com\/document\/d\/1U7WK73YUxDxH4fSh6h1Ki_ZOqUR5VIbFYXQ2uiT0jAM\/edit#bookmark=id.7aeqbyd7ww9u\"> <span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #0563c1; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(Alhasani et al., 2023)<\/span><\/a><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">. This simplicity makes it difficult to be in a position to achieve high diagnostic and prognostic accuracy using the conventional statistical or deterministic techniques in a consistent manner<\/span><a style=\"text-decoration: none;\" href=\"https:\/\/docs.google.com\/document\/d\/1U7WK73YUxDxH4fSh6h1Ki_ZOqUR5VIbFYXQ2uiT0jAM\/edit#bookmark=id.gm4rcsl1sxq2\"> <span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #0563c1; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(Hasan et al., 2020)<\/span><\/a><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">.<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Data mining applications have now become such a critical component of the medical research area and it can be applied to uncover hidden patterns<\/span><a style=\"text-decoration: none;\" href=\"https:\/\/docs.google.com\/document\/d\/1U7WK73YUxDxH4fSh6h1Ki_ZOqUR5VIbFYXQ2uiT0jAM\/edit#bookmark=id.ega1pig2rdc\"> <span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #0563c1; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(Yu et al., 2024)<\/span><\/a><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, relationships as well as forecast information within very large and complex data sets<\/span><a style=\"text-decoration: none;\" href=\"https:\/\/docs.google.com\/document\/d\/1U7WK73YUxDxH4fSh6h1Ki_ZOqUR5VIbFYXQ2uiT0jAM\/edit#bookmark=id.3o1vzq4txsdd\"> <span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #0563c1; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(Gupta et al., 2023)<\/span><\/a><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">. ANN, SVM and Decision Trees have been applied to breast cancer datasets and encouraging findings are achieved<\/span><a style=\"text-decoration: none;\" href=\"https:\/\/docs.google.com\/document\/d\/1U7WK73YUxDxH4fSh6h1Ki_ZOqUR5VIbFYXQ2uiT0jAM\/edit#bookmark=id.fc8tw22im6lx\"> <span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #0563c1; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(Idris &amp; Ismail, 2021)<\/span><\/a><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">. Nevertheless, the approaches have limitations in the ability to address the uncertainty, vagueness and inaccuracy of medical data<\/span><a style=\"text-decoration: none;\" href=\"https:\/\/docs.google.com\/document\/d\/1U7WK73YUxDxH4fSh6h1Ki_ZOqUR5VIbFYXQ2uiT0jAM\/edit#bookmark=id.bc3p4m4sxtqz\"> <span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #0563c1; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(Mohanty &amp; Champati)<\/span><\/a><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">. Such clinical features as tumor size, cell uniformity and mitotic rate tend to lack clear demarcating boundaries and hence sharp classification methods can no longer be used to describe any subtle changes<\/span><a style=\"text-decoration: none;\" href=\"https:\/\/docs.google.com\/document\/d\/1U7WK73YUxDxH4fSh6h1Ki_ZOqUR5VIbFYXQ2uiT0jAM\/edit#bookmark=id.wicdmq73epc3\"> <span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #0563c1; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(Kumar et al., 2019)<\/span><\/a><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">.<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">The solution to this problem can be offered by fuzzy logic, as it allows a possibility to be partly a member of more than one category<\/span><a style=\"text-decoration: none;\" href=\"https:\/\/docs.google.com\/document\/d\/1U7WK73YUxDxH4fSh6h1Ki_ZOqUR5VIbFYXQ2uiT0jAM\/edit#bookmark=id.l7rvoo9m1lea\"> <span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #0563c1; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(Dubey et al., 2018)<\/span><\/a><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">. When data mining is combined with fuzzy logic, it is possible to make models that are capable of managing uncertainty<\/span><a style=\"text-decoration: none;\" href=\"https:\/\/docs.google.com\/document\/d\/1U7WK73YUxDxH4fSh6h1Ki_ZOqUR5VIbFYXQ2uiT0jAM\/edit#bookmark=id.86jhvtfd1wtz\"> <span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #0563c1; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(Sadeghzadeh, 2017)<\/span><\/a><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, tolerating imprecision and making more accurate and intelligible predictions<\/span><a style=\"text-decoration: none;\" href=\"https:\/\/docs.google.com\/document\/d\/1U7WK73YUxDxH4fSh6h1Ki_ZOqUR5VIbFYXQ2uiT0jAM\/edit#bookmark=id.kqnk34y3z62s\"> <span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #0563c1; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(Goudarzi &amp; Maghooli, 2018)<\/span><\/a><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">. Fuzzy-based data mining models are capable of more precisely assigning patients to diagnostic (Benign or Malignant) and prognostic risk (Low, Moderate, High) groups to aid clinicians in making informed decisions<\/span><a style=\"text-decoration: none;\" href=\"https:\/\/docs.google.com\/document\/d\/1U7WK73YUxDxH4fSh6h1Ki_ZOqUR5VIbFYXQ2uiT0jAM\/edit#bookmark=id.a1nor8swtpdb\"> <span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #0563c1; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(Dutta et al., 2018)<\/span><\/a><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">.<\/span><\/p><ol style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\"><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre; margin-left: -18pt;\" aria-level=\"2\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Objectives of the Study<\/span><\/p><\/li><\/ol><ul style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\"><li dir=\"ltr\" style=\"list-style-type: disc; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">To create a fuzzy-based data mining model that can handle clinical data that is imprecise and ambiguous in order to accurately diagnose breast cancer.<\/span><\/p><\/li><li dir=\"ltr\" style=\"list-style-type: disc; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">To use fuzzy logic and feature-selected clinical features to estimate prognosis risk levels (Low, Moderate, and High) in patients with breast cancer.<\/span><\/p><\/li><li dir=\"ltr\" style=\"list-style-type: disc; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">To assess how well the fuzzy-based model performs in terms of accuracy, sensitivity, specificity, and interpretability when compared to traditional machine learning methods (ANN, SVM, Decision Tree).<\/span><\/p><\/li><\/ul><ol style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\" start=\"2\"><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre; margin-left: -18pt;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">LITERATURE REVIEW<\/span><\/p><\/li><\/ol><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Ahadi, et al. (2017) suggested that breast cancer was a prominent issue in social health and the second cause of cancer-related deaths among women. They emphasized that it was necessary to identify the existence of a tumor early be it benign or malignant in order to cure and improve the chances of survival. The existing techniques of diagnosing like characterizing tumors physically and detecting the presence of gene biomarkers were not accurate. To address this issue the researchers have developed a model on the basis of Mamdani-type fuzzy inference system the coefficients of which are optimized with the assistance of statistical analysis. This system was implemented on the normalized data on breast cancer and the findings revealed that optimized fuzzy inference system tackled the issue of complex cancer prediction more accurately than the conventional approaches <\/span><a style=\"text-decoration: none;\" href=\"https:\/\/docs.google.com\/document\/d\/1U7WK73YUxDxH4fSh6h1Ki_ZOqUR5VIbFYXQ2uiT0jAM\/edit#bookmark=id.429jepj8vj9g\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #0563c1; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: underline; -webkit-text-decoration-skip: none; text-decoration-skip-ink: none; vertical-align: baseline; white-space: pre-wrap;\">\u00a0<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #0563c1; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(Ahadi et al., 2017)<\/span><\/a><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">.<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Dhanaseelan and Sutha (2021) focused their investigation in developing a new fuzzy methodology, referred to as Improved Fuzzy Frequent Pattern Mining (IFFP) to the identification of breast cancer at the early stage of the disease. They observed that the conventional data mining algorithms could not quantify clinical datasets that were quantitative. The proposed IFFP algorithm was applied on Wisconsin Breast Cancer Database (WBCD) to establish significant factors, which lead to breast cancer. They arrived at the conclusion that predictive relevance of the feature of Mitoses was low as compared to the predictive relevance of the feature of Bare Nuclei. Through experimental analysis, IFFP method proved to be better than the state-of-the-art algorithms in terms of runtime efficiency and memory consumption<\/span><a style=\"text-decoration: none;\" href=\"https:\/\/docs.google.com\/document\/d\/1U7WK73YUxDxH4fSh6h1Ki_ZOqUR5VIbFYXQ2uiT0jAM\/edit#bookmark=id.gpngf2l8fg9r\"> <span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #0563c1; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(Dhanaseelan, and Sutha, 2021)<\/span><\/a><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">.<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Apasiya, et al. (2024) examined the formation of Enhanced Mobile-based Fuzzy Expert System (EMFES) to predict breast cancer. They noted that the existing systems of diagnosis were inclined to rely on the type-1 fuzzy logic and were not mobile based to facilitate real time data collection and feedback. Type-2 fuzzy logic was applied in this research that would improve accuracy and address uncertainty in the information more effectively. This paper compared the Mamdani and Sugeno inference method and implemented the system using Python programming. Results indicated that the EMFES was in a position to dynamically generate fuzzy rules, abreast with the existing research and generate a mobile-enabled solution that could be used to encourage early diagnosis and risk evaluation, which could reduce deaths resulting to breast cancer<\/span><a style=\"text-decoration: none;\" href=\"https:\/\/docs.google.com\/document\/d\/1U7WK73YUxDxH4fSh6h1Ki_ZOqUR5VIbFYXQ2uiT0jAM\/edit#bookmark=id.tx22vd5lazsj\"> <span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #0563c1; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(Apasiya, et al., 2024)<\/span><\/a><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">.<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Nilashi, et al. (2017) presented a knowledge-based framework of breast cancer classification through clustering and noise removal and fuzzy rule-based classification. Expectation Maximization (EM) was used to cluster and Classification and Regression Trees (CART) was used to generate fuzzy rules. Principal Component Analysis (PCA) was included to resolve multi-collinearity in the data. The system was tested on Wisconsin Diagnostic Breast Cancer and Mammographic Mass datasets. They found that the proposed knowledge-based system was far superior regarding diagnostic accuracy, and could be used effectively as a clinical decision support aid<\/span><a style=\"text-decoration: none;\" href=\"https:\/\/docs.google.com\/document\/d\/1U7WK73YUxDxH4fSh6h1Ki_ZOqUR5VIbFYXQ2uiT0jAM\/edit#bookmark=id.hisuqf3jmxz4\"> <span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #0563c1; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(Nilashi et al., 2017)<\/span><\/a><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">.<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Ojha and Goel (2017) undertook the research on predicting the occurrence of breast cancer on the basis of assisting prognosis. The dataset they employed was the Wisconsin Prognosis Breast Cancer distributed in the UCI machine learning repository and the two classifiers that they applied included the random forest and Deep Neural Network. They showed that the highest prediction accuracy was achieved with the Random Forest classifier, in contrast to the current procedures, and it is necessary to note that the new and well-developed machine learning tools are significant in the context of the prognosis and recurrence prediction<\/span><a style=\"text-decoration: none;\" href=\"https:\/\/docs.google.com\/document\/d\/1U7WK73YUxDxH4fSh6h1Ki_ZOqUR5VIbFYXQ2uiT0jAM\/edit#bookmark=id.6g5jkz5u5iz0\"> <span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #0563c1; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(Ojha &amp; Goel, 2017)<\/span><\/a><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">.<\/span><\/p><ol style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\" start=\"3\"><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre; margin-left: -18pt;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">RESEARCH METHODOLOGY<\/span><\/p><ol style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\"><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre; margin-left: -54pt;\" aria-level=\"2\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Research Design<\/span><\/p><\/li><\/ol><\/li><\/ol><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">The research design employed is a quantitative and predictive research design to investigate ways in which fuzzy-based data mining techniques can be utilized in the diagnosis and prognosis of breast cancer. This design is appropriate since it allows structuring an investigation of the clinical characteristics effectively and creating the prognostic models, which can possibly categorize the occurrence of an illness and predict the degree of the risk.\u00a0<\/span><\/p><ol style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\" start=\"2\"><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre; margin-left: -18pt;\" aria-level=\"2\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Data Collection<\/span><\/p><\/li><\/ol><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">The research involves the simulation of 250 patient records in order to replicate real clinical records in the study of breast cancer. Types of information in the dataset are as follows:<\/span><\/p><ul style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\"><li dir=\"ltr\" style=\"list-style-type: disc; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Tumor characteristics: Size, texture, shape, cell uniformity, mitotic rate, etc.<\/span><\/p><\/li><li dir=\"ltr\" style=\"list-style-type: disc; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Diagnostic markers: Appropriate clinical signs in evaluation of breast cancer.<\/span><\/p><\/li><li dir=\"ltr\" style=\"list-style-type: disc; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Outcome variables: Diagnosis (Benign or Malignant) and Prognosis Risk (Low, Moderate, High).<\/span><\/p><\/li><\/ul><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Preparation steps of data:<\/span><\/p><ul style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\"><li dir=\"ltr\" style=\"list-style-type: disc; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Simulation of realistic patient records using the clinical ranges as reported in the literature.<\/span><\/p><\/li><li dir=\"ltr\" style=\"list-style-type: disc; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Preprocessing to address missing and inconsistency values.<\/span><\/p><\/li><\/ul><ul style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\"><li dir=\"ltr\" style=\"list-style-type: disc; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Encoding fuzzy analysis encoding features- encode numerical and categorical variables into linguistic terms fuzzification.<\/span><\/p><\/li><\/ul><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">This methodology can be applied in real patient data in practice, although in this case, ethical considerations (anonymization, informed consent, confidentiality of clinical data) must be considered.<\/span><\/p><ol style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\" start=\"3\"><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre; margin-left: -18pt;\" aria-level=\"2\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Data Preparation<\/span><\/p><\/li><\/ol><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Before the modeling, the dataset is pre-processed to facilitate quality and consistency:<\/span><\/p><ul style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\"><li dir=\"ltr\" style=\"list-style-type: disc; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Missing values would be imputed with either mean or mode imputation based on the type of feature.<\/span><\/p><\/li><li dir=\"ltr\" style=\"list-style-type: disc; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Categorical variables are coded into numerical or language variables that can be analyzed through fuzzy.<\/span><\/p><\/li><li dir=\"ltr\" style=\"list-style-type: disc; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Outliers are detected and handled to avoid distorted model performance. Attributes are normalized where needed to normalize the level of measurement.<\/span><\/p><\/li><\/ul><ol style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\" start=\"4\"><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre; margin-left: -18pt;\" aria-level=\"2\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Feature Selection<\/span><\/p><\/li><\/ol><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">The feature selection is performed in order to maximize the performance of a model, its interpretability, and efficiency:<\/span><\/p><ul style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\"><li dir=\"ltr\" style=\"list-style-type: disc; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Correlation Analysis: Correlated features are very much identified and redundant variables are removed to reduce multicollinearity.<\/span><\/p><\/li><li dir=\"ltr\" style=\"list-style-type: disc; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Fuzzy Entropy Measures: Features are assessed on the basis of their informational value to diagnosis and prognosis. Not very relevant variables are eliminated in order to maximize the input feature set.<\/span><\/p><\/li><\/ul><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">The step will guarantee that the fuzzy-based model concentrates on the most informative clinical properties and minimize the computational complexity.<\/span><\/p><ol style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\" start=\"5\"><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre; margin-left: -18pt;\" aria-level=\"2\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Fuzzy-Based Data Mining Model<\/span><\/p><\/li><\/ol><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">The steps involved in the construction process of the fuzzy-based classifier are only a couple of steps:<\/span><\/p><ol style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\"><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: 'Times New Roman',serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Fuzzification:<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> With the help of the fuzzy membership functions, the continuous clinical variables (e.g., tumor size, mitotic rate) are fuzzified into the linguistic values (Low, Medium or High). This allows the model to be able to withstand natural uncertainty and imprecision of medical information.<\/span><\/p><\/li><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: 'Times New Roman',serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Rule Generation:<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> Fuzzy rules are developed according to the data and the combinations of the clinical features are also translated into the results (diagnose\/ benign\/ malignant) or the prognosis (low\/ moderate\/ high) risk.<\/span><\/p><\/li><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: 'Times New Roman',serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Inference Engine:<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> The fuzzy inference engine considers all the rules that are available to a given patient record and then takes the output and combines the output to generate a fuzzy output on whether the disease is likely to occur or whether the disease carries a high risk.<\/span><\/p><\/li><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: 'Times New Roman',serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Defuzzification:<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> The fuzzy values are converted to crisp values, which provide a result that can be acted upon, e.g. Malignant or High-Risk to be used in clinical decision-making.<\/span><\/p><\/li><\/ol><ol style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\" start=\"6\"><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre; margin-left: -18pt;\" aria-level=\"2\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Model Evaluation<\/span><\/p><\/li><\/ol><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">The data mining model which is fuzzy is tested through 10-fold cross-validation to facilitate healthy and unbiased judgment. The metrics calculated are the following:<\/span><\/p><ul style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\"><li dir=\"ltr\" style=\"list-style-type: disc; font-size: 12pt; font-family: 'Times New Roman',serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Accuracy:<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> Overall proportion of correct predictions.<\/span><\/p><\/li><\/ul><ul style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\"><li dir=\"ltr\" style=\"list-style-type: disc; font-size: 12pt; font-family: 'Times New Roman',serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Sensitivity (Recall):<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> The model has the capability to detect positive cases in an appropriate manner.<\/span><\/p><\/li><li dir=\"ltr\" style=\"list-style-type: disc; font-size: 12pt; font-family: 'Times New Roman',serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Specificity:<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> The model can detect negative cases in the right way.<\/span><\/p><\/li><li dir=\"ltr\" style=\"list-style-type: disc; font-size: 12pt; font-family: 'Times New Roman',serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Precision:<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> Proportion of true positives among predicted positive cases.<\/span><\/p><\/li><li dir=\"ltr\" style=\"list-style-type: disc; font-size: 12pt; font-family: 'Times New Roman',serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">F1-Score:<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> Precision and recall in the same direction, and on a 0-1 scale, harmonic mean between the two.<\/span><\/p><\/li><\/ul><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">The fuzzy-based classifier is compared to other classic models of data mining such as Artificial Neural Networks (ANN), Support Vector Machines (SVM) and Decision Trees to evaluate their comparative performances in respect to the diagnostic and prognosis model.<\/span><\/p><ol style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\" start=\"4\"><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre; margin-left: -18pt;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">DATA ANALYSIS AND INTERPRETATION\u00a0<\/span><\/p><\/li><\/ol><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">The clinical data plays a critical role in the trends and risk factors analysis of breast cancer. The data set of 250 simulated patient record provides valuable data on tumor properties, cell uniformity, mitosis and other diagnostic characteristics, which are essential to diagnosis and prognosis.<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"><br \/><\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Table 1: Sample Dataset<\/span><\/p><div dir=\"ltr\" style=\"margin-left: 0pt;\" align=\"center\"><table style=\"border: none; border-collapse: collapse;\"><colgroup><col width=\"85\" \/><col width=\"80\" \/><col width=\"134\" \/><col width=\"110\" \/><col width=\"88\" \/><col width=\"127\" \/><\/colgroup><tbody><tr style=\"height: 0pt;\"><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Patient ID<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Tumor Size (cm)<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Cell Uniformity<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Mitotic Rate<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Diagnosis<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Prognosis Risk<\/span><\/p><\/td><\/tr><tr style=\"height: 0pt;\"><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">1<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">2.3<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Medium<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Low<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Benign<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Low-Risk<\/span><\/p><\/td><\/tr><tr style=\"height: 0pt;\"><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">2<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">5.7<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">High<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">High<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Malignant<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">High-Risk<\/span><\/p><\/td><\/tr><tr style=\"height: 0pt;\"><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">3<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">3.8<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Medium<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Medium<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Malignant<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Moderate-Risk<\/span><\/p><\/td><\/tr><tr style=\"height: 0pt;\"><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">\u2026<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">\u2026<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">\u2026<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">\u2026<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">\u2026<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">\u2026<\/span><\/p><\/td><\/tr><tr style=\"height: 0pt;\"><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">248<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">3.5<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Medium<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Medium<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Malignant<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Moderate-Risk<\/span><\/p><\/td><\/tr><tr style=\"height: 0pt;\"><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">249<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">2.2<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Low<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Low<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Benign<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Low-Risk<\/span><\/p><\/td><\/tr><tr style=\"height: 0pt;\"><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">250<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">5.6<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">High<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">High<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Malignant<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">High-Risk<\/span><\/p><\/td><\/tr><\/tbody><\/table><\/div><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Table 1 presents a sample of the patient data and demonstrates the distribution of the clinical characteristics and its results. According to the sample, large tumor size, consistent formation of the cells and high mitotic rate are predominantly malignant and predisposes to lower prognosis (Moderate-Risk or High-Risk). Conversely, small tumor sized patients, low uniformity of cell and low mitotic rate are mostly regarded as benign, and of low prognosis risk. The fluctuation and disparity of breast cancer data is also revealed in the table of intermediate cases wherein the moderate tumor size and regularity of the cells are linked to the Moderate-Risk prognosis. Such a disparity shows that fuzzy-based data mining algorithms will be required, and they can be effectively applied to uncertainty and imprecision to classify and make more accurate predictions of the outcomes of patients. Overall, the dataset indicates the existence of a clear correlation between clinical characteristics and the severity of the disease to build predictive models on early diagnosis and risk assessment.<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Figure 1 shows the fuzzy membership functions that will be utilized in this research in order to transform the quantitative clinical variables into the linguistic ones (Low, Medium, High), which will allow the model to cope with the uncertainties and imprecision inherent in medical data.<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"><br \/><\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"><span style=\"border: none; display: inline-block; overflow: hidden; width: 423px; height: 230px;\"><img fetchpriority=\"high\" decoding=\"async\" style=\"margin-left: 0px; margin-top: 0px;\" 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width=\"423\" height=\"230\" \/><\/span><\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Figure 1: <\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Fuzzy Membership Functions<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"><br \/><\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">The figure 1 shows that the three important clinical features, i.e., the size of the tumor, the uniformity of the cells, and the rate of mitosis have the following membership values in the fuzzy categories. As an example, the size of tumors is a full member (1) of the Low category with values in range 0-3 cm, partial member (0.7) of the medium category, and zero member of High category, not in terms of rigid thresholds. Equally, there are overlapping membership between cell uniformity and mitotic rate in the Medium and High ranges to represent the imprecision in the actual patient measurements. These fuzzy memberships enable the classifier to estimate patient records more selectively and elastic, with the level of a feature that is a member of two or more categories. This is the foundation of the fuzzy rule generation which enhances the accuracy and interpretability of the prediction of breast cancer diagnosis and prognosis.<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Figure 2 provides the performance comparison of various models used in the diagnosis of breast cancer on 250 samples of patients, measuring variables like accuracy, sensitivity, specificity, precision and F1-score.<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"><br \/><\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"><span style=\"border: none; display: inline-block; overflow: hidden; width: 537px; height: 282px;\"><img decoding=\"async\" style=\"margin-left: 0px; margin-top: 0px;\" 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width=\"537\" height=\"282\" \/><\/span><\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Figure 2: <\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Performance Comparison (Diagnosis)<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"><br \/><\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Based on the figure 2, it can be seen that the fuzzy based classifier performs better than other conventional models such as Artificial Neural Networks (ANN) and Support Vector Machines (SVM) in all evaluation metrics. The fuzzy model (94 percent most precise) indicates that it can better classify more patients (than ANN 91 percent) and SVM (89 percent). Its sensitivity (95) means that it has the power of detecting malignant cases accurately and its specificity (93) means that it has the power of detecting benign cases accurately. In addition, high accuracy (94%), F1-score (94.5), demonstrates that it has an equal correlation between true positive and false positive, which is very precise in clinical diagnosis. The effectiveness of such a high performance could be attributed by the fact that the fuzzy system is capable of operating on uncertainty and overlaps of values of clinical features and can make more subtle decisions during the diagnosis process. In general, figure 2 reveals that the fuzzy-based methods of data mining offer a stronger and more precise framework of breast cancer diagnostics as compared to traditional machine learning models.<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Figure 3 provides a comparison of various models in prediction of breast cancer based on 250 patient samples, with the evaluation of various measures such as accuracy, sensitivity, specificity, precision and F1-score.<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"><br \/><\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"><span style=\"border: none; display: inline-block; overflow: hidden; width: 554px; height: 274px;\"><img decoding=\"async\" style=\"margin-left: 0px; margin-top: 0px;\" 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\" width=\"554\" height=\"274\" \/><\/span><\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Figure 3: <\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Performance Comparison (Prognosis)<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"><br \/><\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Figure 3 demonstrates that the fuzzy-based classifier has a better performance in predicting the risk of prognosis than ANN and Decision Tree models. A fuzzy model with 92 percent accuracy indicates that the fuzzy model is reliable in general prediction of patient risk levels. Its sensitivity (91) means that it is highly able to recognize higher-risk patients, whereas its specificity (93) shows that it can recognize low-risk patients. In addition, high precision (92%) and F1-score (91.5) indicate the balance in the model in terms of the number of correctly predicted risk cases and false predictions, which makes the prognosis evaluation reliable. The better performance of the fuzzy classifier is explained with its capacity to cope with uncertainty and overlapping of clinical feature values thus providing subtle classification of patients into Low, Moderate and High-Risk categories. In sum, figure 3 supports the idea that fuzzy-driven data mining methods offer a solid and explainable model of breast cancer prognosis to support clinical decision-making and individual patient care.<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Table 2 shows the confusion matrix of breast cancer diagnosis with the fuzzy-based classifier, where the number of correctly and erroneously classified cases of benign and malignant patients are shown.<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"><br \/><\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Table 2: <\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Confusion Matrix (Diagnosis \u2013 Fuzzy Classifier)<\/span><\/p><div dir=\"ltr\" style=\"margin-left: 0pt;\" align=\"center\"><table style=\"border: none; border-collapse: collapse;\"><colgroup><col width=\"199\" \/><col width=\"195\" \/><col width=\"229\" \/><\/colgroup><tbody><tr style=\"height: 0pt;\"><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\">\u00a0<\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Predicted Benign<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Predicted Malignant<\/span><\/p><\/td><\/tr><tr style=\"height: 0pt;\"><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Actual Benign<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">70<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">4<\/span><\/p><\/td><\/tr><tr style=\"height: 0pt;\"><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Actual Malignant<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">5<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">71<\/span><\/p><\/td><\/tr><\/tbody><\/table><\/div><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Based on the table 2, the fuzzy-based classifier successfully recognizes 70 of 74 benign cases and 71 of 76 malignant cases, which implies that the classifier has a high degree of diagnostic accuracy. The model falsely assigns 4 benign and 5 malignant cases as benign and malignant respectively, which is a fairly low error. This proves that the fuzzy classifier is very useful in distinguishing between benign and malignant tumors with high sensitivity (capacity to detect malignant cases) and specificity (capacity to detect benign cases). The confusion matrix validates that the fuzzy system is able to process overlapping and uncertain clinical data and give trustworthy and interpretable diagnostic forecasts to clinical decision-making.<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Table 3 shows the confusion matrix of the breast cancer prognosis provided by the fuzzy-based classifier, and the assignment of the risk level correctly and incorrectly (Low-Risk, Moderate-Risk, High-Risk) of 250 patient samples.<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"><br \/><\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Table 3: <\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Confusion Matrix (Prognosis \u2013 Fuzzy Classifier)<\/span><\/p><div dir=\"ltr\" style=\"margin-left: 0pt;\" align=\"center\"><table style=\"border: none; border-collapse: collapse;\"><colgroup><col width=\"118\" \/><col width=\"81\" \/><col width=\"118\" \/><col width=\"85\" \/><\/colgroup><tbody><tr style=\"height: 0pt;\"><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\">\u00a0<\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Low-Risk<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Moderate-Risk<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">High-Risk<\/span><\/p><\/td><\/tr><tr style=\"height: 0pt;\"><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Low-Risk<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">60<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">5<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">2<\/span><\/p><\/td><\/tr><tr style=\"height: 0pt;\"><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Moderate-Risk<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">4<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">55<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">6<\/span><\/p><\/td><\/tr><tr style=\"height: 0pt;\"><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">High-Risk<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">1<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">4<\/span><\/p><\/td><td style=\"vertical-align: top; padding: 0pt 5.4pt 0pt 5.4pt; overflow: hidden; overflow-wrap: break-word; border: solid #000000 0.5pt;\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: center; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">63<\/span><\/p><\/td><\/tr><\/tbody><\/table><\/div><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">As shown in the table 3, the fuzzy-based model predicts 60\/67 Low-Risk cases, 55\/65 Moderate-Risk cases and 63\/68 High-Risk cases, indicating a strong predictive ability of the model across all types of risks. Misclassifications are also not high and there are Low-Risk patients who are predicted to be Moderate or High-Risk and few Moderate-Risk patients who are predicted to be Low or High-Risk. This shows that the fuzzy system is valuable in a situation with overlapping clinical characteristics and uncertainty of patient data and can help us subjectively divide the patients into different risk levels. The validation of the confusion matrix has demonstrated that the fuzzy classifier can give plausible and readable prognosis, which is useful in terms of individualized treatment planning and proactive patient management.<\/span><\/p><ol style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\" start=\"5\"><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre; margin-left: -18pt;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">DISCUSSION<\/span><\/p><\/li><\/ol><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">The findings from this study strongly support the use of fuzzy-based data mining methods as a highly effective method for the diagnosis and prognosis of breast cancer. The diagnosis and risk prediction of breast cancer is always difficult due to the variability of clinical presentations and the uncertainty and imprecision of medical data. While many common machine learning algorithms &#8211; such as ANN, SVM, and Decision Trees &#8211; will sometimes utilize crisp thresholds or deterministic rules, they can miss finer subtleties of patient information. Fuzzy-based models use fuzzy logic to measure clinical variables on a continuum and represent quantitative clinical data in qualitative linguistic terms, thus giving the modeling process a more appropriate and flexible structure of clinical information found in the real world.<\/span><\/p><ul style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\"><li dir=\"ltr\" style=\"list-style-type: disc; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Dataset Analysis and Clinical Insights:<\/span><\/p><\/li><\/ul><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Table 1 analyzing the 250 patient records showed that there were different patterns between clinical attributes and outcomes. Large tumors, high mitotic rates, and uniformity of cells were mainly defined as malignant and classified as Moderate or High-Risk prognoses. On the other hand, patients whose tumors were less large, those with low mitotic activity and more homogenous cells were predominantly benign and low-risk. Surprisingly, the intermediate cases with moderate tumor conditions showed inconsistency in prognosis, and a system of classification that can accommodate gradual change and overlap is well handled in the fuzzy-based models.<\/span><\/p><ul style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\"><li dir=\"ltr\" style=\"list-style-type: disc; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Role of Fuzzy Membership Functions:<\/span><\/p><\/li><\/ul><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">The membership functions (Figure 1) which were used to translate the continuous variables into the linguistic variables (Low, Medium and High) were used to give a framework. The overlapping membership values enabled the model to explain borderline cases in which a patient may have clinical characteristics that do not fit well in a single category. A tumor size of 3.5 cm might be in the Low and Medium category, for instance, and this would allow the classifier to make subtle predictions. It is based on this process of fuzzification, which generates the basis of rule generation, in which several clinical features are used to determine the probability of malignancy or the level of risk.<\/span><\/p><ul style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\"><li dir=\"ltr\" style=\"list-style-type: disc; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Model Performance and Comparative Analysis:<\/span><\/p><\/li><\/ul><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">The performance of the fuzzy-based classifier is better than the ANN, SVM, and Decision Trees in both diagnosis (Figure 2) and prognosis (Figure 3). There is high accuracy (94% diagnosis, 92% prognosis), high sensitivity and specificity, which means that the fuzzy model can be confident to detect both malignant as well as benign cases and correctly predict the risk level of the patient. The high precision and F1-scores also indicate the balanced nature of the model to reduce false positive and false negative. These findings point to the power of fuzzy logic to deal with uncertainty, imprecision, and overlapping clinical characteristics, which are prevalent in breast cancer data sets.<\/span><\/p><ul style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\"><li dir=\"ltr\" style=\"list-style-type: disc; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Confusion Matrix Insights:<\/span><\/p><\/li><\/ul><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Table 2 and Table 3 are confusion matrices that provide a close-up look at model predictions. In diagnosis, few benign and malignant cases were misdiagnosed, which highlights the strength of the fuzzy classifier. The model is found to accurately classify the majority of patients in Low, Moderate, and High-Risk groups in the process of prognosis prediction with the only considerable misclassifications made in the case of intermediate risk groups. These results affirm that fuzzy-based systems have interpretable and reliable predictions which is vital in making clinical decisions.<\/span><\/p><ul style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\"><li dir=\"ltr\" style=\"list-style-type: disc; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Clinical Relevance and Implications:<\/span><\/p><\/li><\/ul><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">The fuzzy-based method facilitates customized treatment of patients. When clinicians are proper in their categorization of patients into refined risk groups, they are able to adjust treatment plans, focus on high-risk patients in terms of monitoring and reassure the patients who are at low risk. Clinicians can also interpret the reasoning behind predictions, which makes them more confident in automated decision-support systems due to the interpretability of fuzzy rules.<\/span><\/p><ul style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\"><li dir=\"ltr\" style=\"list-style-type: disc; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Strengths and Limitations:<\/span><\/p><\/li><\/ul><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">The chief advantage of this research is that it combines the benefits of fuzzy logic with data mining approaches, which include flexibility, interpretability, and the predictive power. Selection of features also improved the efficiency of the models by targeting the most informative attributes. The drawback is, however, the use of simulated data which, though representative of clinical ranges, may not be quite representative of the complexity of real-world populations of patients. The next avenue of work is validation with large-scale, real clinical datasets, with perhaps ensemble learning approaches and real-time tracking to enhance predictive performance.<\/span><\/p><ol style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\" start=\"6\"><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre; margin-left: -18pt;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: bold; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">CONCLUSION<\/span><\/p><\/li><\/ol><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">This research has shown that the fuzzy-based data mining methods offer an efficient and credible tool of breast cancer diagnosis and prognosis. Through the use of fuzzy logic, the proposed model is able to manage the underlying ambiguity, imprecision and overlapping trends inherent in clinical data that are in most cases difficult to address using traditional machine learning models. The fuzzy-based classifier is very accurate, sensitive, specific, precise, and had high F1-scores in the diagnosis and prognosis tasks, more so than the traditional models of ANN, SVM, and Decision Trees. Further high model interpretability and efficiency were achieved due to the feature selection and fuzzy rule generation, which enabled subtle classification of patients into low, moderate, and high-risk groups. The confusion matrix analysis indicated that there were only a few misclassifications which validated the strength and accuracy of the model in making clinical decisions. Altogether, the results indicate that fuzzy-based data mining enhances predictive accuracy as well as provides practical value that can be used to manage a patient individually, detect diseases at an early stage, and plan proactive treatment. The next step in the work should be to validate the model using real-world clinical data, integrate ensemble learning methods, and consider real-time predictive applications in order to further enhance its clinical relevance and influence on healthcare outcomes.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-fcde522 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"fcde522\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-0e9d0b4\" data-id=\"0e9d0b4\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-91ff56f elementor-widget elementor-widget-heading\" data-id=\"91ff56f\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h6 class=\"elementor-heading-title elementor-size-default\">Statements &amp; Declarations\n<\/h6>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-45eda8b elementor-widget elementor-widget-text-editor\" data-id=\"45eda8b\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Author\u2019s Contribution: Parul Bhatnagar was responsible for data collection, algorithm implementation, and primary manuscript drafting. Dr. Bhupendra Kumar provided supervisory oversight, refined the fuzzy logic models, and performed the final technical review.<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Peer Review: This article has undergone a double-blind peer-review process organized by the Editorial Board of <\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Shodh Sari-An International Multidisciplinary Journal<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">. Reviewers and authors remained mutually anonymous.<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Competing Interests: The authors declare that they have no financial or personal interests that could be viewed as influencing the results or discussion reported in this paper.<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Funding: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Data Availability: The datasets and fuzzy-based models analyzed during this study are available from the corresponding author on reasonable request.<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Ethical Approval: This research utilizes secondary, anonymized medical datasets for computational modeling and does not involve direct human trials or animal experimentation.<\/span><\/p><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 8pt;\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">License: This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) License, Published by ICERT.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-f11fb23 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"f11fb23\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-c5f3733\" data-id=\"c5f3733\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-cc704ff elementor-widget elementor-widget-heading\" data-id=\"cc704ff\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h6 class=\"elementor-heading-title elementor-size-default\">References\n<\/h6>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f41de1d elementor-widget elementor-widget-text-editor\" data-id=\"f41de1d\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ol style=\"margin-top: 0; margin-bottom: 0; padding-inline-start: 48px;\"><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre; margin-left: -18pt;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Ahadi, F. 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A fuzzy rule\u2010based system with decision tree for breast cancer detection. <\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">IET Image Processing, 17<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(7), 2083\u20132096.\u00a0<\/span><\/p><\/li><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre; margin-left: -18pt;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Hasan, T. M., Mohammed, S. D., &amp; Waleed, J. (2020). Development of breast cancer diagnosis system based on fuzzy logic and probabilistic neural network. <\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Eastern-European Journal of Advanced Technologies, 4<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(9\u2013106), 6\u201313.\u00a0<\/span><\/p><\/li><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre; margin-left: -18pt;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Idris, N. 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Breast cancer disease classification using fuzzy-ID3 algorithm with FUZZYDBD method: Automatic fuzzy database definition. <\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">PeerJ Computer Science, 7<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, e427.\u00a0<\/span><\/p><\/li><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre; margin-left: -18pt;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Kumar, M., Kulkarni, A. J., &amp; Satapathy, S. C. (2019). A hybridized data clustering for breast cancer prognosis and risk exposure using fuzzy C-means and cohort intelligence. In <\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Optimization in Machine Learning and Applications<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> (pp. 113\u2013126). Springer Singapore.\u00a0<\/span><\/p><\/li><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre; margin-left: -18pt;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Mohanty, H., &amp; Champati, S. (2023). A robust classification model using fuzzy logic: Successful prediction of breast cancer patients. <\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Recent Trends in Applied Mathematics in Science and Engineering, 2819<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(1), 060005.\u00a0<\/span><\/p><\/li><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre; margin-left: -18pt;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Nilashi, M., Ibrahim, O., Ahmadi, H., &amp; Shahmoradi, L. (2017). A knowledge-based system for breast cancer classification using fuzzy logic method. <\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Telematics and Informatics, 34<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(4), 133\u2013144.\u00a0<\/span><\/p><\/li><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre; margin-left: -18pt;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Ojha, U., &amp; Goel, S. (2017, January). A study on prediction of breast cancer recurrence using data mining techniques. In <\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">2017 7th International Conference on Cloud Computing, Data Science &amp; Engineering &#8211; Confluence<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> (pp. 527\u2013530). IEEE.\u00a0<\/span><\/p><\/li><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre; margin-left: -18pt;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Oskouei, R. J., Kor, N. M., &amp; Maleki, S. A. (2017). Data mining and medical world: Breast cancers\u2019 diagnosis, treatment, prognosis and challenges. <\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">American Journal of Cancer Research, 7<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(3), 610\u2013624.<\/span><\/p><\/li><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre; margin-left: -18pt;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Rajendran, K., Jayabalan, M., Thiruchelvam, V., &amp; Sivakumar, V. (2019). Feasibility study on data mining techniques in diagnosis of breast cancer. <\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">International Journal of Machine Learning and Computing, 9<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">(3), 328\u2013333.\u00a0<\/span><\/p><\/li><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre; margin-left: -18pt;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Roshani, F., Turksen, I. B., Zarandi, M. F., &amp; Maftooni, M. (2015, August). Fuzzy expert system for prognosis of breast cancer recurrence. In <\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">2015 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS) held jointly with 2015 5th World Conference on Soft Computing (WConSC)<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> (pp. 1\u20135). IEEE.\u00a0<\/span><\/p><\/li><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre; margin-left: -18pt;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Sadeghzadeh, M. (2017, September). A new method for diagnosing breast cancer using firefly algorithm and fuzzy rule-based classification. In <\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">2017 IEEE 11th International Conference on Application of Information and Communication Technologies (AICT)<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\"> (pp. 1\u20135). IEEE.\u00a0<\/span><\/p><\/li><li dir=\"ltr\" style=\"list-style-type: decimal; font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre; margin-left: -18pt;\" aria-level=\"1\"><p dir=\"ltr\" style=\"line-height: 1.7999999999999998; text-align: justify; margin-top: 0pt; margin-bottom: 0pt;\" role=\"presentation\"><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Yu, X., Tian, J., Chen, Z., Meng, Y., &amp; Zhang, J. (2024). Predictive breast cancer diagnosis using ensemble fuzzy model. <\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: italic; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">Image and Vision Computing, 148<\/span><span style=\"font-size: 12pt; font-family: Arial,sans-serif; color: #000000; background-color: transparent; font-weight: 400; font-style: normal; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;\">, 105146.\u00a0<\/span><\/p><\/li><\/ol>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-fc1adc8 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"fc1adc8\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-64691ca\" data-id=\"64691ca\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap\">\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-7bf65a2\" data-id=\"7bf65a2\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-1d9f75e elementor-widget elementor-widget-elementskit-social-share\" data-id=\"1d9f75e\" data-element_type=\"widget\" data-widget_type=\"elementskit-social-share.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"ekit-wid-con\" >\t\t<ul class=\"ekit_socialshare\">\n                            <li class=\"elementor-repeater-item-db288b3\" data-social=\"facebook\">\n                    <div class=\"facebook\">\n                        \n                        <i aria-hidden=\"true\" class=\"icon icon-facebook\"><\/i>                        \n                                                                                            <\/div>\n                <\/li>\n                                            <li class=\"elementor-repeater-item-8c1acc4\" data-social=\"whatsapp\">\n                    <div class=\"whatsapp\">\n                        \n                        <i aria-hidden=\"true\" class=\"icon icon-whatsapp-1\"><\/i>                        \n                                                                                            <\/div>\n                <\/li>\n                                            <li class=\"elementor-repeater-item-a0e5dae\" data-social=\"linkedin\">\n                    <div class=\"linkedin\">\n                        \n                        <i aria-hidden=\"true\" class=\"icon icon-linkedin\"><\/i>                        \n                                                                                            <\/div>\n                <\/li>\n                                    <\/ul>\n        <\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-9b0fea0\" data-id=\"9b0fea0\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-6a02fba elementor-align-right elementor-widget elementor-widget-button\" data-id=\"6a02fba\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/icert.org.in\/index.php\/shodh-sari-2\/shodh-sari-vol5-issue-1\/\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Back<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Shodh Sari-An International Multidisciplinary Journal Vol-05, Issue-02(Apr &#8211; Jun 2026) An International scholarly\/ academic journal, peer-reviewed\/ refereed journal, ISSN : 2959-1376 Application Of Fuzzy-Based Data Mining Techniques in Breast Cancer Diagnosis and Prognosis Bhatnagar, Parul1 and Kumar, Bhupendra2 1Research Scholar, School of Computer Science &amp; Applications, IIMT University Meerut, Uttar Pradesh, India 2Professor, School of [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"elementor_header_footer","format":"standard","meta":{"_acf_changed":false,"postBodyCss":"","postBodyMargin":[],"postBodyPadding":[],"postBodyBackground":{"backgroundType":"classic","gradient":""},"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"disabled","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[1],"tags":[],"class_list":["post-33453","post","type-post","status-publish","format-standard","hentry","category-uncategorised"],"acf":[],"_links":{"self":[{"href":"https:\/\/icert.org.in\/index.php\/wp-json\/wp\/v2\/posts\/33453","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/icert.org.in\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/icert.org.in\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/icert.org.in\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/icert.org.in\/index.php\/wp-json\/wp\/v2\/comments?post=33453"}],"version-history":[{"count":15,"href":"https:\/\/icert.org.in\/index.php\/wp-json\/wp\/v2\/posts\/33453\/revisions"}],"predecessor-version":[{"id":33491,"href":"https:\/\/icert.org.in\/index.php\/wp-json\/wp\/v2\/posts\/33453\/revisions\/33491"}],"wp:attachment":[{"href":"https:\/\/icert.org.in\/index.php\/wp-json\/wp\/v2\/media?parent=33453"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/icert.org.in\/index.php\/wp-json\/wp\/v2\/categories?post=33453"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/icert.org.in\/index.php\/wp-json\/wp\/v2\/tags?post=33453"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}