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<!DOCTYPE html> <html > <head> <meta charset="utf-8"> <meta rel="search" type="application/opensearchdescription+xml" href="/open_search.xml" title="Academia.edu"> <meta content="width=device-width, initial-scale=1" name="viewport"> <meta name="google-site-verification" content="bKJMBZA7E43xhDOopFZkssMMkBRjvYERV-NaN4R6mrs"> <meta name="csrf-param" content="authenticity_token" /> <meta name="csrf-token" content="ekCeLWqxQWBgic5ywMXDwN9NNR3P2ozbyR8R9Gzxx8qKMYShVQTOdtq/4tCCYbkU7tafqqkpcq060NIYOY7Vbg==" /> <meta name="citation_title" content="Hybrid model based on Decision Trees and Fuzzy Cognitive Maps for Medical Decision Support System" /> <meta name="citation_journal_title" content="IFMBE Proceedings" /> <meta name="citation_author" content="Papageorgiou, Elpiniki" /> <meta name="citation_author" content="Stylios, C. D." /> <meta name="citation_author" content="Groumpos, P. 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Conceptual decision making models with the potential of learning capabilities are more appropriate and suitable for" /> <meta property="article:author" content="https://teiep.academia.edu/Chrysostomosstylios" /> <meta name="description" content="For medical decision making processes (diag- nosing, classification, etc.) all decisions must be made effec- tively and reliably. Conceptual decision making models with the potential of learning capabilities are more appropriate and suitable for" /> <title>(PDF) “Hybrid model based on Decision Trees and Fuzzy Cognitive Maps for Medical Decision Support System” | Chrysostomos Stylios - Academia.edu</title> <link rel="canonical" href="https://www.academia.edu/4394404/_Hybrid_model_based_on_Decision_Trees_and_Fuzzy_Cognitive_Maps_for_Medical_Decision_Support_System_" /> <script async src="https://www.googletagmanager.com/gtag/js?id=G-5VKX33P2DS"></script> <script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'G-5VKX33P2DS', { cookie_domain: 'academia.edu', send_page_view: false, }); gtag('event', 'page_view', { 'controller': "single_work", 'action': "show", 'controller_action': 'single_work#show', 'logged_in': 'false', 'edge': 'unknown', // Send nil if there is no A/B test bucket, in case some records get logged // with missing data - that way we can distinguish between the two cases. // ab_test_bucket should be of the form <ab_test_name>:<bucket> 'ab_test_bucket': null, }) </script> <script> var $controller_name = 'single_work'; var $action_name = "show"; var $rails_env = 'production'; var $app_rev = '49879c2402910372f4abc62630a427bbe033d190'; var $domain = 'academia.edu'; var $app_host = "academia.edu"; var $asset_host = "academia-assets.com"; var $start_time = new Date().getTime(); var $recaptcha_key = "6LdxlRMTAAAAADnu_zyLhLg0YF9uACwz78shpjJB"; var $recaptcha_invisible_key = "6Lf3KHUUAAAAACggoMpmGJdQDtiyrjVlvGJ6BbAj"; var $disableClientRecordHit = false; </script> <script> window.require = { config: function() { return function() {} } } </script> <script> window.Aedu = window.Aedu || {}; window.Aedu.hit_data = null; window.Aedu.serverRenderTime = new Date(1732466769000); window.Aedu.timeDifference = new Date().getTime() - 1732466769000; </script> <script type="application/ld+json">{"@context":"https://schema.org","@type":"ScholarlyArticle","abstract":"\u0026amp;amp;amp;quot;For medical decision making processes (diag- nosing, classification, etc.) all decisions must be made effec- tively and reliably. Conceptual decision making models with the potential of learning capabilities are more appropriate and suitable for performing such hard tasks. Decision trees are a well known technique, which has been applied in many medi- cal systems to support decisions based on a set of instances. On the other hand, the soft computing technique of Fuzzy Cogni- tive Maps (FCMs) is an effective decision making technique, which provides high performance with a conceptual represen- tation of gathered knowledge a nd existing experience. FCMs have been used for medical decision making with emphasis in radiotherapy and classification tasks for bladder tumour grad- ing. This paper proposes and presents an hybrid model de- rived from the combination and the synergistic application of the above mentioned techniques. The proposed Decision Tree- Fuzzy Cognitive Map model has enhanced operation and effec- tiveness based on both methods giving better accuracy results in medical decision tasks. \u0026amp;amp;amp;quot;","author":[{"@context":"https://schema.org","@type":"Person","name":"Chrysostomos Stylios"}],"contributor":[],"dateCreated":"2013-09-02","dateModified":"2014-05-30","datePublished":null,"headline":"“Hybrid model based on Decision Trees and Fuzzy Cognitive Maps for Medical Decision Support System”","inLanguage":"en","keywords":[],"locationCreated":"Seoul, Korea","publication":null,"publisher":{"@context":"https://schema.org","@type":"Organization","name":null},"image":null,"thumbnailUrl":null,"url":"https://www.academia.edu/4394404/_Hybrid_model_based_on_Decision_Trees_and_Fuzzy_Cognitive_Maps_for_Medical_Decision_Support_System_","sourceOrganization":[{"@context":"https://schema.org","@type":"EducationalOrganization","name":"teiep"}]}</script><link rel="stylesheet" media="all" 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"https://www.academia.edu/login?post_login_redirect_url=https%3A%2F%2Fwww.academia.edu%2F4394404%2F_Hybrid_model_based_on_Decision_Trees_and_Fuzzy_Cognitive_Maps_for_Medical_Decision_Support_System_%3Fauto%3Ddownload"; window.loswp.translateUrl = "https://www.academia.edu/login?post_login_redirect_url=https%3A%2F%2Fwww.academia.edu%2F4394404%2F_Hybrid_model_based_on_Decision_Trees_and_Fuzzy_Cognitive_Maps_for_Medical_Decision_Support_System_%3Fshow_translation%3Dtrue"; window.loswp.previewableAttachments = [{"id":31824908,"identifier":"Attachment_31824908","shouldShowBulkDownload":false}]; window.loswp.shouldDetectTimezone = true; window.loswp.shouldShowBulkDownload = true; window.loswp.showSignupCaptcha = false window.loswp.willEdgeCache = false; window.loswp.work = {"work":{"id":4394404,"created_at":"2013-09-02T22:38:36.296-07:00","from_world_paper_id":null,"updated_at":"2021-12-11T08:11:38.843-08:00","_data":{"abstract":"For medical decision\r\nmaking processes (diag-\r\nnosing, classification, etc.) all decisions must be made effec-\r\ntively and reliably. Conceptual decision making models with\r\nthe potential of learning capabilities are more appropriate and\r\nsuitable for performing such hard\r\ntasks. Decision trees are a\r\nwell known technique, which has been applied in many medi-\r\ncal systems to support decisions based on a set of instances. On\r\nthe other hand, the soft computing technique of Fuzzy Cogni-\r\ntive Maps (FCMs) is an effective decision making technique,\r\nwhich provides high performance with a conceptual represen-\r\ntation of gathered knowledge a\r\nnd existing experience. FCMs\r\nhave been used for medical decision making with emphasis in\r\nradiotherapy and classification\r\ntasks for bladder tumour grad-\r\ning. This paper proposes and\r\npresents an hybrid model de-\r\nrived from the combination and\r\nthe synergistic application of\r\nthe above mentioned techniques.\r\nThe proposed Decision Tree-\r\nFuzzy Cognitive Map model has\r\nenhanced operation and effec-\r\ntiveness based on both methods\r\ngiving better accuracy results\r\nin medical decision tasks. ","location":"Seoul, Korea ","more_info":"World Congress on Medical Physics and Biomedical Engineering 2006, WC 2006 Congress","conference_end_date":"2006,9,1","conference_start_date":"2006,8,27"},"document_type":"conference_presentation","pre_hit_view_count_baseline":0,"quality":"high","language":"en","title":"“Hybrid model based on Decision Trees and Fuzzy Cognitive Maps for Medical Decision Support System” ","broadcastable":false,"draft":null,"has_indexable_attachment":true,"indexable":true}}["work"]; window.loswp.workCoauthors = [713166]; window.loswp.locale = "en"; window.loswp.countryCode = "SG"; window.loswp.cwvAbTestBucket = ""; window.loswp.designVariant = "ds_vanilla"; window.loswp.fullPageMobileSutdModalVariant = "control"; window.loswp.useOptimizedScribd4genScript = false; window.loswp.appleClientId = 'edu.academia.applesignon';</script><script defer="" src="https://accounts.google.com/gsi/client"></script><div class="ds-loswp-container"><div class="ds-work-card--grid-container"><div class="ds-work-card--container js-loswp-work-card"><div class="ds-work-card--cover"><div class="ds-work-cover--wrapper"><div class="ds-work-cover--container"><button class="ds-work-cover--clickable js-swp-download-button" data-signup-modal="{"location":"swp-splash-paper-cover","attachmentId":31824908,"attachmentType":"pdf"}"><img alt="First page of ““Hybrid model based on Decision Trees and Fuzzy Cognitive Maps for Medical Decision Support System” ”" class="ds-work-cover--cover-thumbnail" src="https://0.academia-photos.com/attachment_thumbnails/31824908/mini_magick20190425-15036-i5ogaf.png?1556257357" /><img alt="PDF Icon" class="ds-work-cover--file-icon" src="//a.academia-assets.com/assets/single_work_splash/adobe.icon-574afd46eb6b03a77a153a647fb47e30546f9215c0ee6a25df597a779717f9ef.svg" /><div class="ds-work-cover--hover-container"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span><p>Download Free PDF</p></div><div class="ds-work-cover--ribbon-container">Download Free PDF</div><div class="ds-work-cover--ribbon-triangle"></div></button></div></div></div><div class="ds-work-card--work-information"><h1 class="ds-work-card--work-title">“Hybrid model based on Decision Trees and Fuzzy Cognitive Maps for Medical Decision Support System” </h1><div class="ds-work-card--work-authors ds-work-card--detail"><a class="ds-work-card--author js-wsj-grid-card-author ds2-5-body-md ds2-5-body-link" data-author-id="713166" href="https://teiep.academia.edu/Chrysostomosstylios"><img alt="Profile image of Chrysostomos Stylios" class="ds-work-card--author-avatar" src="//a.academia-assets.com/images/s65_no_pic.png" />Chrysostomos Stylios</a></div><p class="ds-work-card--work-abstract ds-work-card--detail ds2-5-body-md">For medical decision making processes (diag- nosing, classification, etc.) all decisions must be made effec- tively and reliably. Conceptual decision making models with the potential of learning capabilities are more appropriate and suitable for performing such hard tasks. Decision trees are a well known technique, which has been applied in many medi- cal systems to support decisions based on a set of instances. On the other hand, the soft computing technique of Fuzzy Cogni- tive Maps (FCMs) is an effective decision making technique, which provides high performance with a conceptual represen- tation of gathered knowledge a nd existing experience. FCMs have been used for medical decision making with emphasis in radiotherapy and classification tasks for bladder tumour grad- ing. This paper proposes and presents an hybrid model de- rived from the combination and the synergistic application of the above mentioned techniques. The proposed Decision Tree- Fuzzy Cognitive Map model has enhanced operation and effec- tiveness based on both methods giving better accuracy results in medical decision tasks. </p><div class="ds-work-card--button-container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--work-card","attachmentId":31824908,"attachmentType":"pdf","workUrl":"https://www.academia.edu/4394404/_Hybrid_model_based_on_Decision_Trees_and_Fuzzy_Cognitive_Maps_for_Medical_Decision_Support_System_"}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--work-card","attachmentId":31824908,"attachmentType":"pdf","workUrl":"https://www.academia.edu/4394404/_Hybrid_model_based_on_Decision_Trees_and_Fuzzy_Cognitive_Maps_for_Medical_Decision_Support_System_"}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div></div><div data-auto_select="false" data-client_id="331998490334-rsn3chp12mbkiqhl6e7lu2q0mlbu0f1b" data-doc_id="31824908" data-landing_url="https://www.academia.edu/4394404/_Hybrid_model_based_on_Decision_Trees_and_Fuzzy_Cognitive_Maps_for_Medical_Decision_Support_System_" data-login_uri="https://www.academia.edu/registrations/google_one_tap" data-moment_callback="onGoogleOneTapEvent" id="g_id_onload"></div><div class="ds-top-related-works--grid-container"><div class="ds-related-content--container ds-top-related-works--container"><h2 class="ds-related-content--heading">Related papers</h2><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="0" data-entity-id="22824118" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/22824118/A_Combined_Fuzzy_Cognitive_Map_and_Decision_Trees_Model_for_Medical_Decision_Making">A Combined Fuzzy Cognitive Map and Decision Trees Model for Medical Decision Making</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="7629591" href="https://teiste.academia.edu/ElpinikiPapageorgiou">Elpiniki Papageorgiou</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2006 International Conference of the IEEE Engineering in Medicine and Biology Society, 2006</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A Combined Fuzzy Cognitive Map and Decision Trees Model for Medical Decision Making","attachmentId":43369411,"attachmentType":"pdf","work_url":"https://www.academia.edu/22824118/A_Combined_Fuzzy_Cognitive_Map_and_Decision_Trees_Model_for_Medical_Decision_Making","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/22824118/A_Combined_Fuzzy_Cognitive_Map_and_Decision_Trees_Model_for_Medical_Decision_Making"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="1" data-entity-id="31459580" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/31459580/Fuzzy_Cognitive_Maps_Structure_for_Medical_Decision_Support_Systems">Fuzzy Cognitive Maps Structure for Medical Decision Support Systems</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="713166" href="https://teiep.academia.edu/Chrysostomosstylios">Chrysostomos Stylios</a></div><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Fuzzy Cognitive Maps Structure for Medical Decision Support Systems","attachmentId":51816568,"attachmentType":"pdf","work_url":"https://www.academia.edu/31459580/Fuzzy_Cognitive_Maps_Structure_for_Medical_Decision_Support_Systems","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/31459580/Fuzzy_Cognitive_Maps_Structure_for_Medical_Decision_Support_Systems"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="2" data-entity-id="4394443" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/4394443/_Novel_Architecture_for_supporting_medical_decision_making_of_different_data_types_based_on_Fuzzy_Cognitive_Map_Framework_">“Novel Architecture for supporting medical decision making of different data types based on Fuzzy Cognitive Map Framework”</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="713166" href="https://teiep.academia.edu/Chrysostomosstylios">Chrysostomos Stylios</a></div><p class="ds-related-work--abstract ds2-5-body-sm">Medical problems involve different types of variables and data, which have to be processed, analyzed and synthesized in order to reach a decision and/or conclude to a diagnosis. Usually, information and data set are both symbolic and numeric but most of the well-known data analysis methods deal with only one kind of data. Even when fuzzy approaches are considered, which are not depended on the scales of variables, usually only numeric data is considered. The medical decision support methods usually are accessed in only one type of available data. Thus, sophisticated methods have been proposed such as integrated hybrid learning approaches to process symbolic and numeric data for the decision support tasks. Fuzzy Cognitive Maps (FCM) is an efficient modelling method, which is based on human knowledge and experience and it can handle with uncertainty and it is constructed by extracted knowledge in the form of fuzzy rules. The FCM model can be enhanced if a fuzzy rule base (IF-THEN rules) is available. This rule base could be derived by a number of machine learning and knowledge extraction methods. Here it is introduced a hybrid attempt to handle situations with different types of available medical and /or clinical data and with difficulty to handle them for decision support tasks using soft computing techniques.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"“Novel Architecture for supporting medical decision making of different data types based on Fuzzy Cognitive Map Framework”","attachmentId":31824927,"attachmentType":"pdf","work_url":"https://www.academia.edu/4394443/_Novel_Architecture_for_supporting_medical_decision_making_of_different_data_types_based_on_Fuzzy_Cognitive_Map_Framework_","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/4394443/_Novel_Architecture_for_supporting_medical_decision_making_of_different_data_types_based_on_Fuzzy_Cognitive_Map_Framework_"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="3" data-entity-id="22836476" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/22836476/A_study_on_Fuzzy_Cognitive_Map_structures_for_Medical_Decision_Support_Systems">A study on Fuzzy Cognitive Map structures for Medical Decision Support Systems</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="31758301" href="https://teiep.academia.edu/CStylios">Chrysostomos Stylios</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Proceedings of the 8th conference of the European Society for Fuzzy Logic and Technology, 2013</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A study on Fuzzy Cognitive Map structures for Medical Decision Support Systems","attachmentId":43381544,"attachmentType":"pdf","work_url":"https://www.academia.edu/22836476/A_study_on_Fuzzy_Cognitive_Map_structures_for_Medical_Decision_Support_Systems","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/22836476/A_study_on_Fuzzy_Cognitive_Map_structures_for_Medical_Decision_Support_Systems"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="4" data-entity-id="4195074" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/4195074/Fuzzy_cognitive_map_architectures_for_medical_decision_support_systems"> Fuzzy cognitive map architectures for medical decision support systems</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="713166" href="https://teiep.academia.edu/Chrysostomosstylios">Chrysostomos Stylios</a></div><p class="ds-related-work--abstract ds2-5-body-sm">Medical decision support systems can provide assistance in crucial clinical judgments, particularly for inexperienced medical professionals. Fuzzy cognitive maps (FCMs) is a soft computing technique for modeling complex systems, which follows an approach similar to human reasoning and the human decision-making process. FCMs can successfully represent knowledge and human experience, introducing concepts to represent the essential elements and the cause and effect relationships among the concepts to model the behavior of any system. Medical decision systems are complex systems that can be decomposed to non-related and related subsystems and elements, where many factors have to be taken into consideration that may be complementary, contradictory, and competitive; these factors influence each other and determine the overall clinical decision with a different degree. Thus, FCMs are suitable for medical decision support systems and appropriate FCM architectures are proposed and developed as well as the corresponding examples from two medical disciplines, i.e. speech and language pathology and obstetrics, are described.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":" Fuzzy cognitive map architectures for medical decision support systems","attachmentId":31691315,"attachmentType":"pdf","work_url":"https://www.academia.edu/4195074/Fuzzy_cognitive_map_architectures_for_medical_decision_support_systems","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/4195074/Fuzzy_cognitive_map_architectures_for_medical_decision_support_systems"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="5" data-entity-id="13340590" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/13340590/Clinical_Decision_Support_System_based_on_Fuzzy_Cognitive_Maps">Clinical Decision Support System based on Fuzzy Cognitive Maps</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="32580297" href="https://obs-vlfr.academia.edu/DrDoualiNassim">Nassim Douali</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Journal of Computer Science & Systems Biology, 2015</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Clinical Decision Support System based on Fuzzy Cognitive Maps","attachmentId":38018771,"attachmentType":"pdf","work_url":"https://www.academia.edu/13340590/Clinical_Decision_Support_System_based_on_Fuzzy_Cognitive_Maps","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/13340590/Clinical_Decision_Support_System_based_on_Fuzzy_Cognitive_Maps"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="6" data-entity-id="4195080" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/4195080/Complementary_case_based_reasoning_and_competitive_Fuzzy_cognitive_maps_for_advanced_medical_decisions">Complementary case-based reasoning and competitive Fuzzy cognitive maps for advanced medical decisions</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="713166" href="https://teiep.academia.edu/Chrysostomosstylios">Chrysostomos Stylios</a></div><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Complementary case-based reasoning and competitive Fuzzy cognitive maps for advanced medical decisions","attachmentId":31691318,"attachmentType":"pdf","work_url":"https://www.academia.edu/4195080/Complementary_case_based_reasoning_and_competitive_Fuzzy_cognitive_maps_for_advanced_medical_decisions","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/4195080/Complementary_case_based_reasoning_and_competitive_Fuzzy_cognitive_maps_for_advanced_medical_decisions"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="7" data-entity-id="4392569" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/4392569/_Medical_Decision_Support_Systems_based_on_Soft_Computing_Techniques_">“Medical Decision Support Systems based on Soft Computing Techniques”</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="713166" href="https://teiep.academia.edu/Chrysostomosstylios">Chrysostomos Stylios</a></div><p class="ds-related-work--abstract ds2-5-body-sm">Medical Decision Support Systems (MDSS) are very important constructions that are incorporated into Intelligent Information E - Health Systems aiming to produce warning s or to consult and suggest clinical ju dgments either to inexperienced medical professionals or in their light er versions to the general public through medical advisors websites . Soft Computing (SC) techniques , especially th ose that are based on exploit ing human knowledge and experience , are extr emely useful to model complex decision making procedures and thus , they have a key role in development such MDSS. Such a modeling methodology i s Fuzzy Cognitive Maps which is suitable to represent human reasoning and to infer conclusions and decisions in a human - like way. In order to develop an integrated stand alone MDSS, Fuzzy Cognitive Maps could be complemented by other Soft Computing techniques such as Genetic Algorithms and/ or Case Based Reasoning and so to construct more efficient advanced Medical De cision Support Systems. The synergism and complementary of these methodologies may pave the way to new sophisticated systems.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"“Medical Decision Support Systems based on Soft Computing Techniques”","attachmentId":31823759,"attachmentType":"pdf","work_url":"https://www.academia.edu/4392569/_Medical_Decision_Support_Systems_based_on_Soft_Computing_Techniques_","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/4392569/_Medical_Decision_Support_Systems_based_on_Soft_Computing_Techniques_"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="8" data-entity-id="28091011" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/28091011/Fuzzy_Decision_Trees_in_medical_decision_Making_Support_System">Fuzzy Decision Trees in medical decision Making Support System</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="52653817" href="https://zilina.academia.edu/ElenaZaitseva">Elena Zaitseva</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2012 Federated Conference on Computer Science and Information Systems, 2012</p><p class="ds-related-work--abstract ds2-5-body-sm">ABSTRACT Decision Making Support System based on Fuzzy Logic is considered in this paper for oncology disease diagnosis. The decision making procedure corresponds to the recognition (classification) of the new case by analyzing a set of instances (already solved cases) for which classes are known. Ontology (solved cases) is defined as Fuzzy Classification Rules that are formed by different Fuzzy Decision Trees. Three types of Fuzzy Decision Trees (Non-ordered, ordered and Stable) are considered in the paper. Induction of these Fuzzy Decision Trees is based on Cumulative Information Estimates. The proposed approach is implemented based on medical problem benchmark with real clinical data for breast cancer diagnosis.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Fuzzy Decision Trees in medical decision Making Support System","attachmentId":54951340,"attachmentType":"pdf","work_url":"https://www.academia.edu/28091011/Fuzzy_Decision_Trees_in_medical_decision_Making_Support_System","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/28091011/Fuzzy_Decision_Trees_in_medical_decision_Making_Support_System"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="9" data-entity-id="3069799" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/3069799/Medical_decision_making_through_fuzzy_computational_intelligent_approaches">Medical decision making through fuzzy computational intelligent approaches</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="1418969" href="https://teilam.academia.edu/ElpinikiPapageorgiou">Elpiniki Papageorgiou</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2009</p><p class="ds-related-work--abstract ds2-5-body-sm">Abstract. A new approach for the construction of Fuzzy Cognitive Maps augmented by knowledge through fuzzy rule-extraction methods for medical decision making is investigated. This new approach develops an augmented Fuzzy Cognitive Mapping based Decision Support System combining knowledge from experts and knowledge from data in the form of fuzzy rules generated from rule-based knowledge discovery methods.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Medical decision making through fuzzy computational intelligent approaches","attachmentId":30997065,"attachmentType":"pdf","work_url":"https://www.academia.edu/3069799/Medical_decision_making_through_fuzzy_computational_intelligent_approaches","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/3069799/Medical_decision_making_through_fuzzy_computational_intelligent_approaches"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div></div></div><div class="ds-sticky-ctas--wrapper js-loswp-sticky-ctas hidden"><div class="ds-sticky-ctas--grid-container"><div class="ds-sticky-ctas--container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--sticky-ctas","attachmentId":31824908,"attachmentType":"pdf","workUrl":null}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--sticky-ctas","attachmentId":31824908,"attachmentType":"pdf","workUrl":null}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div><div class="ds-below-fold--grid-container"><div class="ds-work--container js-loswp-embedded-document"><div class="attachment_preview" data-attachment="Attachment_31824908" style="display: none"><div class="js-scribd-document-container"><div class="scribd--document-loading js-scribd-document-loader" style="display: block;"><img alt="Loading..." src="//a.academia-assets.com/images/loaders/paper-load.gif" /><p>Loading Preview</p></div></div><div style="text-align: center;"><div class="scribd--no-preview-alert js-preview-unavailable"><p>Sorry, preview is currently unavailable. 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