Skin Lesion

Skin lesion analysis focuses on the automated diagnosis and segmentation of skin lesions from images, primarily to aid in early cancer detection. Current research emphasizes improving model accuracy and fairness using various deep learning architectures, including convolutional neural networks (CNNs), vision transformers (ViTs), and generative adversarial networks (GANs), often incorporating techniques like ensemble learning, multi-modal data fusion, and unsupervised domain adaptation to address data scarcity and bias. These advancements aim to improve diagnostic accuracy, reduce ethnic disparities in prediction, and enhance the interpretability of AI-driven diagnoses, ultimately leading to better patient outcomes and more efficient healthcare.