Melanoma Diagnosis

Melanoma diagnosis research focuses on improving the accuracy and reliability of automated detection systems, primarily using deep learning models like convolutional neural networks and vision transformers, to aid dermatologists. Current efforts concentrate on enhancing model explainability, addressing biases in training data, and incorporating contextual information from multiple images to improve diagnostic confidence and generalization across diverse datasets. These advancements hold significant potential for earlier and more accurate melanoma detection, ultimately improving patient outcomes and reducing mortality rates associated with this aggressive skin cancer.