An ensemble of neural networks for breast cancer diagnosis

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dc.contributor.authorYavuz, Erdem
dc.contributor.authorEyüpoğlu, Can
dc.contributor.authorŞanver, Ufuk
dc.contributor.authorYazıcı, Rıfat
dc.date.accessioned2020-11-21T15:56:13Z
dc.date.available2020-11-21T15:56:13Z
dc.date.issued2017en_US
dc.departmentİstanbul Ticaret Üniversitesien_US
dc.description2nd International Conference on Computer Science and Engineering, UBMK 2017 -- 5 October 2017 through 8 October 2017 -- -- 132116en_US
dc.description.abstractSince breast cancer is a common disease in society all over the world, early diagnosis is of vital importance in order to treat patients before it reaches an irreversible phase. Expert systems are being developed to make it easier to diagnose the disease. In this study, an ensemble of neural networks named radial basis function network (RBFN), generalized regression neural network (GRNN) and feed forward neural network (FFNN) is implemented to separate breast cancer data samples into benign/malignant classes. The utilities of these common methods and the proposed hybrid model which is a combination of these methods are explored and their performances are comparatively presented. The experimental results on Wisconsin Diagnostic Breast Cancer (WDBC) dataset have proven that the proposed method presents a promise for diagnosis of breast cancer. The proposed model can be used as a tool to assist medical specialists in making their decision on the disease. © 2017 IEEE.en_US
dc.identifier.doi10.1109/UBMK.2017.8093456en_US
dc.identifier.endpage543en_US
dc.identifier.isbn9781540000000
dc.identifier.scopus2-s2.0-85040586515en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage538en_US
dc.identifier.urihttps://doi.org/10.1109/UBMK.2017.8093456
dc.identifier.urihttps://hdl.handle.net/11467/4106
dc.identifier.wosWOS:000426856900100en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof2nd International Conference on Computer Science and Engineering, UBMK 2017en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBreast cancer diagnosisen_US
dc.subjectExpert systemen_US
dc.subjectFeed forward neural networken_US
dc.subjectGeneralized regression neural networken_US
dc.subjectRadial basis function networken_US
dc.titleAn ensemble of neural networks for breast cancer diagnosisen_US
dc.typeConference Objecten_US

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