The rapid advancements in artificial intelligence (AI) have significantly impacted modern healthcare

particularly for skin cancer detection in the field of dermatology. Skin cancer has become a considerable public health challenge

highlighting the importance of early detection to improve patient outcomes. AI models have revolutionized skin cancer diagnosis by enhancing the accuracy and efficiency of detecting malignancies in the early stages. This review provides a comprehensive comparison of the latest AI technologies used in skin cancer detection

including segmentation

classification

and reinforcement learning models. It also explores the integration of transformer and multimodal technologies

which have further refined the diagnostic process. Despite the remarkable progress

challenges remain in the practical deployment of these AI models

especially those concerning data diversity

model interpretability

and clinical integration. Future research directions should focus on overcoming these limitations to fully harness AI’s potential in dermatology

aiming to increase diagnostic accuracy

reduce healthcare costs

and ultimately save lives.