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 Üniversitesi
dc.descriptionMedical Technologies National Conference (TIPTEKNO) -- OCT 27-29, 2016 -- Antalya, TURKEY
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.
dc.identifier.isbn978-1-5090-2386-8
dc.identifier.scopus2-s2.0-85016128349
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://hdl.handle.net/11501/1491
dc.identifier.wosWOS:000455003600068
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isotr
dc.publisherIEEE
dc.relation.ispartof2016 Medical Technologies National Conference (Tiptekno)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectMachine Learning
dc.subjectBreast Cancer Diagnosis
dc.subjectMicroarray
dc.subjectFeature Selection
dc.titleMachine Learning Based Performance Development for Diagnosis of Breast Cancer
dc.typeConference Object

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