Performance Analysis of Machine Learning Algorithm for Skin Disease Detection

This paper examines how AI algorithms can improve dermatology diagnosis. It finds visual analysis, the current method, to be subjective and proposes AI as a data-driven solution with higher accuracy. Focusing on machine learning algorithms like Support Vector Machine, CNN, Logistic regression the report explores how dimensionality reduction aids in efficient model training. Analysis of a skin cancer image dataset revealed promising results, with most algorithms achieving accuracy in the range of 85% to 93% for classifying both benign and malignant.