Review of Skin disease classification using machine learning methods

A significant worldwide health issue with a large population is skin disease. The advancement of dermatological predictive categorization has grown more accurate and predictive in recent years due to the rapid growth of technology and the use of various data mining approaches. Therefore, it is crucial to develop machine learning approaches that can classify skin diseases differently and effectively. So far, no machine learning technique has performed better than the others in terms of predicting skin diseases. Due to its physical and psychological impact on individuals, skin diseases are a serious and concerning problem in communities. Early skin disease detection is crucial for effective therapy. The ability and experience of the specialist doctor is relevant to the process of identifying and treating skin damage. Diagnostic procedures need to be precise and timely. Through the application of machine learning algorithms and the utilisation of the enormous amount of data present in healthcare facilities and hospitals, artificial intelligence research has recently been utilised in the field of diagnosing skin diseases. The classification of skin diseases using machine learning was the subject of a large number of earlier studies that were compiled in this research