Skin Lesion Classification using Machine Learning Algorithms

dc.contributor.authorOzkan, Ilker Ali
dc.contributor.authorKoklu, Murat
dc.date.accessioned2020-03-26T19:32:34Z
dc.date.available2020-03-26T19:32:34Z
dc.date.issued2017
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractMelanoma is a deadly skin cancer that breaks out in the skin’s pigment cells on the skin surface. Melanoma causes 75% of the skin cancer-related deaths. This disease can be diagnosed by a dermatology specialist through the interpretation of the dermoscopy images in accordance with ABCD rule. Even if dermatology experts use dermatological images for diagnosis, the rate of the correct diagnosis of experts is estimated to be 75-84%. The purpose of this study is to pre-classify the skin lesions in three groups as normal, abnormal and melanoma by machine learning methods and to develop a decision support system that should make the decision easier for a doctor. The objective of this study is skin lesions based on dermoscopic images PH2 datasets using 4 different machine learning methods namely; ANN, SVM, KNN and Decision Tree. Correctly classified instances were found as 92.50%, 89.50%, 82.00% and 90.00% for ANN, SVM, KNN and DT respectively. The findings show that the system developed in this study has the feature of a medical decision support system which can help dermatologists in diagnosing of the skin lesionsen_US
dc.identifier.endpage7701en_US
dc.identifier.issn2147-6799en_US
dc.identifier.issn2147-6799en_US
dc.identifier.issue4en_US
dc.identifier.startpage1098en_US
dc.identifier.urihttp://www.trdizin.gov.tr/publication/paper/detail/TWpjeE9EZ3lNZz09
dc.identifier.urihttps://hdl.handle.net/20.500.12395/34496
dc.identifier.volume5en_US
dc.indekslendigikaynakTR-Dizinen_US
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.subjectBilgisayar Bilimlerien_US
dc.subjectYapay Zekaen_US
dc.titleSkin Lesion Classification using Machine Learning Algorithmsen_US
dc.typeArticleen_US

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