Machine Learning Based Performance Development for Diagnosis of Breast Cancer

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dc.authorwosidBabur, Sebahattin/AAA-2147-2020
dc.contributor.authorBektas, Burcu
dc.contributor.authorBabur, Sebahattin
dc.date.accessioned2024-06-13T20:18:41Z
dc.date.available2024-06-13T20:18:41Z
dc.date.issued2015
dc.departmentİstanbul Gedik Üniversitesien_US
dc.descriptionMedical Technologies National Conference (TIPTEKNO) -- OCT 27-29, 2016 -- Antalya, TURKEYen_US
dc.description.abstractBreast cancer is prevalent among women and develops from breast tissue. Early diagnosis and accurate treatment is vital to increase the rate of survival. Identification of genetic factors with microarray technology can make significant contributions to diagnosis and treatment process. In this study, several machine learning algorithms are used for Diagnosis of Breast Cancer and their classification performances are compared with each other. In addition, the active genes in breast cancer are identified by attribute selection methods and the conducted study show success rate 90,72 % with 139 feature.en_US
dc.identifier.isbn978-1-5090-2386-8
dc.identifier.scopus2-s2.0-85016128349en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://hdl.handle.net/11501/1491
dc.identifier.wosWOS:000455003600068en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isotren_US
dc.publisherIEEEen_US
dc.relation.ispartof2016 Medical Technologies National Conference (Tiptekno)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMachine Learningen_US
dc.subjectBreast Cancer Diagnosisen_US
dc.subjectMicroarrayen_US
dc.subjectFeature Selectionen_US
dc.titleMachine Learning Based Performance Development for Diagnosis of Breast Canceren_US
dc.typeConference Objecten_US

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