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dc.contributor.authorBirtane, Sibelen_US
dc.contributor.authorCanayaz, Emreen_US
dc.contributor.authorAltıkardeş, Zehra Aysunen_US
dc.contributor.authorKorkmaz, Hayriyeen_US
dc.date.accessioned2019-07-25T12:54:53Z
dc.date.available2019-07-25T12:54:53Z
dc.date.issued2017en_US
dc.identifier.citationBirtane, S., Canayaz, E., Altikardes, Z. A., Korkmaz, H., & Ieee. (2017). Development of Decision Support System Using Mamdani Type Fuzzy Logic Clusters for Metabolic Syndrome Risk Assesment. New York: Ieee.en_US
dc.identifier.isbn9781538606339
dc.identifier.urihttps://hdl.handle.net/20.500.12294/1606
dc.descriptionBirtane, Sibel (Arel Author)en_US
dc.description.abstractToday, with the improvement of socioeconomic conditions, consumption of ready-to-eat foods increased and a more non-mobile lifestyle became widespread. Thus, the incidence of a number of metabolic problems together has begun to increase. These problems arise in the form of bodily changes, deterioration of glucose tolerance, disorders of fat metabolism and blood pressure elevation. It is called the "metabolic syndrome". The metabolic syndrome is a definition that emphasizes the importance of combining some risk factors that increase the development of cardiovascular disease and diabetes, not alone. The aim of this study is to develop a decision support system that helps the doctor working on the data obtained from the demographic and laboratory tests necessary for the diagnosis of the metabolic syndrome. By entering the data of the person through the developed user-interface; it is aimed to determine the risk factor of the person according to the analysis result. In this study, the program was run on the data of 56 patients including 34 female and 22 male, using Mamdani type fuzzy logic clusters in the LabVIEW platform.en_US
dc.language.isoturen_US
dc.publisherIEEEen_US
dc.relation.ispartof2017 Medical Technologies National Congress (TIPTEKNO)en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectFuzzy Logicen_US
dc.subjectDecision Support Systemen_US
dc.subjectMetabolic Sendromeen_US
dc.subjectLabVIEWen_US
dc.titleDevelopment of Decision Support System Using Mamdani Type Fuzzy Logic Clusters for Metabolic Syndrome Risk Assesmenten_US
dc.title.alternativeMamdani Tip Bulanık Mantık Kümeleri Kullanılarak Metabolik Sendrom Risk Tespit Karar Destek Sisteminin Geliştirilmesien_US
dc.typeconferenceObjecten_US
dc.departmentMeslek Yüksekokulu, Bilgisayar Programcılığı Programıen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.coverage.doi10.1109/TIPTEKNO.2017.8238035


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