Kaplan, AliGuldogan, EmekColak, CemilArslan, Ahmet K.2024-08-042024-08-042019https://doi.org/10.1109/idap.2019.8875970https://hdl.handle.net/11616/103884International Conference on Artificial Intelligence and Data Processing (IDAP) -- SEP 21-22, 2019 -- Inonu Univ, Malatya, TURKEYRecently, hospitals and health care institutions have increasingly been addressing clinical decision support systems (CDSS), which can offer specific patient assessments or recommendations to physicians and health care professionals. It is very useful to develop CDSS which can help physicians to make meaningful and correct decisions by using existing data or image sets. Also, CDSS increases the diagnostic accuracy of diseases, provides significant facilities in precision medicine applications, increases operating efficiency of hospitals and reduces costs. In this context, the proposed project intends to create a model usingpre-trained networks (i.e. VGG-16,) based on deep learning (DL) that can successfully predict the melanoma using dermoscopic images. The current study provides clinical support to physicians in the medical decision-making process for the diagnosis of melanoma.trinfo:eu-repo/semantics/closedAccessClassificationDeep-learningMelanomaKerasDermoscopic imagingConference Object10.1109/idap.2019.8875970WOS:000591781100097N/A