Classification of Melanocytic Skin Lesions Using Machine Learning Techniques

Accurate diagnosis of skin lesions suspected of melanocytosis is important for timely intervention and prevention of malignant transformation. This study examines the performance of various state-of-the-art deep learning models. To detect such lesions such as VGG19, ResNet, Vision Transformer, Sequential Model, EfficientNet, Inception V3, focusing on key performance parameters. A comparative analysis was performed to evaluate Efficiency in identifying high-risk lesions Emphasis is placed on potential clinical applications. The results revealed significant variation in model performance. Several architectures have shown improved diagnostic capabilities. This work provides good insights into the strengths and limitations of these models. Allowing the way for advancements in AI-powered diagnostic tools in dermatology.