Diagnosis of mesothelioma disease using different classification techniques

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dc.contributor.authorTutuncu, Kemal
dc.contributor.authorÇataltaş, Özcan
dc.date.accessioned2020-03-26T19:32:33Z
dc.date.available2020-03-26T19:32:33Z
dc.date.issued2017
dc.departmentSelçuk Üniversitesi, Teknoloji Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.description.abstractMesothelioma, which is a disease of the pleura and peritoneum, is an asbestos-related environmental disease in undevelopedcountries. Although the incidence of this disease is lower than that of lung cancer, the reaction it creates in society is very high. In thisstudy, 9 different classification algorithms of data mining were applied to the Mesethelioma data set obtained from real patients in DicleUniversity, Faculty of Medicine and loaded into UCI Machine Learning Repository, and the results were compared. When the obtainedresults were examined, it has been seen that Artificial Neural Network (ANN) had %99.0740 correct classification ratio.en_US
dc.identifier.citationTutuncu, K., Cataltas, O. (2017). Diagnosis of Mesothelioma Disease Using Different Classification Techniques. International Journal of Intelligent Systems and Applications in Engineering, Special Issue, 7-11.
dc.identifier.endpage11en_US
dc.identifier.issn2147-6799en_US
dc.identifier.issn2147-6799en_US
dc.identifier.issueSpecial Issueen_US
dc.identifier.startpage7en_US
dc.identifier.urihttp://www.trdizin.gov.tr/publication/paper/detail/TXpBM09EZ3dNQT09
dc.identifier.urihttps://hdl.handle.net/20.500.12395/34493
dc.identifier.volume5en_US
dc.indekslendigikaynakTR-Dizinen_US
dc.institutionauthorTutuncu, Kemal
dc.institutionauthorÇataltaş, Özcan
dc.language.isoenen_US
dc.relation.ispartofInternational Journal of Intelligent Systems and Applications in Engineeringen_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectArtificial Neural Networken_US
dc.subjectClassification Algorithmsen_US
dc.subjectClassification Ratio
dc.subjectData Mining
dc.subjectMesothelioma Disease
dc.titleDiagnosis of mesothelioma disease using different classification techniquesen_US
dc.typeArticleen_US

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