Machine Learning Methods in Skin Disease Recognition: A Systematic Review

Skin lesions affect millions of people worldwide. They can be easily recognized based on their typically abnormal texture and color but are difficult to diagnose due similar symptoms among certain types lesions. The motivation for this study is collate analyze machine learning (ML) applications in skin lesion research, with the goal encouraging development automated systems disease diagnosis. To assist dermatologists clinical diagnosis, several image datasets have been developed published online. Such efforts motivated researchers medical staff develop automatic diagnosis using segmentation classification processes. This paper summarizes fundamental steps papers mainly since 2013. ML methods (including traditional deep (DL)) recognition reviewed contributions, methods, achieved results. technical analysis beneficial continuing reliable effective computer-aided systems. We believe that more research will lead current studies being used real settings near future.