Fusion: Practice and Applications FPA 2692-4048 2770-0070 10.54216/FPA https://www.americaspg.com/journals/show/1014 2018 2018 Department of Computer Engineering, Harran University, Sanliurafa, 63300, Turkey Nechirvan Nechirvan Department of Computer Engineering, Harran University, Sanliurafa, 63300, Turkey Mehmet Emin Tenekeci According to the American Society of Clinical Oncology, Computer-Aided Diagnosis (CAD) techniques have the tremendous possibility for the screening and early identification of melanoma. They are evaluated in terms of their current state-of-the-art, as well as current practices, challenges, and prospects in the areas of image screening, pre-processing of an image, segmentation of Region of Interest (ROI), feature extraction, feature selection, and classification of dermoscopic images. It is stated in this study that statistical information and outcomes from the most major implementations that have been reported to date are presented. We investigated the evaluation performance of many classifiers that had been developed specifically for the diagnosis of skin cancer. The fundamental aim of this paper is to develop a framework that will serve as a complete guideline for choosing relevant techniques for various elements of an automatic detection technique. 2022 2022 30 40 10.54216/FPA.070103 https://www.americaspg.com/articleinfo/3/show/1014