Detection of Skin Diseases from Images Using Machine Learning and Deep Learning Techniques

Today, classification of skin diseases based on automated systems by analyzing medical images taken from the affected skin surface is one of the important methods to be studied. Skin diseases are one of the global health problems that is increasing year by year and endangering the lives of many people. Early detection of this disease is crucial in preventing its progression and its consequences. Currently, many studies are being conducted to detect skin diseases at early stages and several solutions are being proposed. In particular, classification of skin diseases based on medical images using intelligent systems is one of the best solutions proposed by researchers. In this research work, the methods, models and algorithms for automatic classification of skin diseases based on computer-aided machine learning (ML) and deep learning (DL) algorithms were analyzed. Also, methods for pre-processing medical images were studied to ensure fast and accurate performance of ML and DL models. As a result of the analysis, comparative tables were developed for further research work to compare the results of previous studies and the accuracy of the models proposed in them. The main goal of the study is to fill the research gap in the application of ML and DL models in skin disease classification. This study will help researchers find better solutions for classifying skin diseases, identify existing problems and recent achievements in the classification.