Prognosis of Prostate Cancer by Artificial Neural Networks

Basit Öğe Kaydı
dc.contributor.authorSarıtaş, İsmail
dc.contributor.authorÖzkan, İlker Ali
dc.contributor.authorSert, İbrahim Ünal
dc.date.accessioned2020-03-26T18:04:51Z
dc.date.available2020-03-26T18:04:51Z
dc.date.issued2010
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractIn this study, an artificial neural network has been devised that yields a prognostic result indicating whether patients have cancer or not using their free prostate-specific antigen, total prostate-specific antigen and age data. Though this system does not diagnose cancer conclusively, it helps the doctor in deciding whether a biopsy is necessary by providing information about whether the patient has prostate cancer or not. Data from 121 patients who were definitively diagnosed with cancer after biopsy were used in devising the system. The results of the definitive diagnoses of the patients and the results of the ANN that was performed were analysed using confusion matrix and ROC analyses. As a result of ANN, which was implemented on the basis of these analyses, success rates of 94.11% and 94.44% were achieved for prognosis of disease and validity, respectively. The ANN, which yielded these high rates of reliability, will help doctors make quick and reliable diagnoses without any risks and make it a better option to monitor patients with low prostate cancer risk on whom biopsies must not be carried out through a policy of wait and see.en_US
dc.description.sponsorshipSelcuk UniversitySelcuk Universityen_US
dc.description.sponsorshipThis study was supported by Selcuk University Coordination Office of Scientific Research Projects (BAP). Moreover, we would like to extend our heartfelt thanks to Prof. Dr. Sumer Baltaci of Ankara University, Faculty of Medicine, and Department of Urology, who assist in the obtainment of the data.en_US
dc.identifier.citationSarıtaş, İ., Özkan, İ. A., Sert, İ. Ü., (2010). Prognosis of Prostate Cancer by Artificial Neural Networks. Expert Systems with Applications, (37), 6646-6650. Doi: 10.1016/j.eswa.2010.03.056
dc.identifier.doi10.1016/j.eswa.2010.03.056en_US
dc.identifier.endpage6650en_US
dc.identifier.issn0957-4174en_US
dc.identifier.issn1873-6793en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage6646en_US
dc.identifier.urihttps://dx.doi.org/10.1016/j.eswa.2010.03.056
dc.identifier.urihttps://hdl.handle.net/20.500.12395/25188
dc.identifier.volume37en_US
dc.identifier.wosWOS:000278424600061en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorSarıtaş, İsmail
dc.institutionauthorÖzkan, İlker Ali
dc.institutionauthorSert, İbrahim Ünal
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofExpert Systems with Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectArtificial neural networken_US
dc.subjectProstate canceren_US
dc.subjectProstate-specific antigenen_US
dc.subjectPrognosis of prostate canceren_US
dc.titlePrognosis of Prostate Cancer by Artificial Neural Networksen_US
dc.typeArticleen_US

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Küçük Resim
İsim:
5188.pdf
Boyut:
317.67 KB
Biçim:
Adobe Portable Document Format
Açıklama:
Makale Dosyası
İndir

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Elektrik Elektronik Mühendisliği/Makale Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu
Üroloji/Makale Koleksiyonu