Skin Lesion Classification

Skin lesion classification aims to automatically identify skin diseases from images, improving diagnostic accuracy and accessibility. Current research heavily utilizes deep learning, focusing on multimodal approaches that integrate dermoscopic and clinical images with patient metadata, and employing transformer-based architectures and diffusion models to enhance robustness and address challenges like imbalanced datasets and domain shift. These advancements are crucial for improving the reliability and efficiency of skin cancer diagnosis, particularly in resource-constrained settings, and for mitigating biases introduced by variations in image acquisition.