Optimizing skin disease diagnosis: harnessing online community data with contrastive learning and clustering techniques.

ABSTRACT: Skin diseases pose significant challenges in China. Internet health forums offer a platform for millions of users to discuss skin diseases and share images for early intervention, leaving large amount of valuable dermatology images. However, data quality and annotation challenges limit the potential of these resources for developing diagnostic models. In this study, we proposed a deep-learning model that utilized unannotated dermatology images from diverse online sources. We adopted a contrastive learning approach to learn general representations from unlabeled images and fine-tuned the model on coarsely annotated images from Internet forums. Our model classified 22 common skin diseases. To improve annotation quality, we used a clustering method with a small set of standardized validation

SUBMITTER: Shen Y 

PROVIDER: S-EPMC10853166 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature