Melan-Dx: a knowledge-enhanced vision-language framework improves differential diagnosis of melanocytic neoplasm pathology.

ABSTRACT: Melanoma is one of the top 5 cancer types, causes most deaths among skin cancers, and can be frequently misdiagnosed. Recent pathology image foundation models remain difficult to make accurate differential diagnosis across over forty melanocytic neoplasm histologic subtypes. Motivated by the diagnostic reasoning process of dermatopathologists, we curated a high-quality image and knowledge corpus database containing 2893 images and 1102 knowledge entries annotated by expert dermatopathologists at the University of Pennsylvania. Leveraging this multi-modal dataset, we present "Melan-Dx", a knowledge-enhanced AI framework that augments frozen pathology vision-language models through retrieval from a curated vision-knowledge database, improving differential diagnosis at both patch and whole-sl

SUBMITTER: Yao J 

PROVIDER: S-EPMC12914046 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature