FairDisCo: Fairer AI in Dermatology via Disentanglement Contrastive Learning. (arXiv:2208.10013v1 [cs.CV])

Deep learning models have achieved great success in automating skin lesion
diagnosis. However, the ethnic disparity in these models' predictions, where
lesions on darker skin types are usually underrepresented and have lower
diagnosis accuracy, receives little attention. In this paper, we propose
FairDisCo, a disentanglement deep learning framework with contrastive learning
that utilizes an additional network branch to remove sensitive attributes, i.e.
skin-type information from representations for fairness and another contrastive
branch to enhance feature extraction. We compare FairDisCo to …

ai arxiv cv dermatology learning