FairCLIP: Harnessing Fairness in Vision-Language Learning

arXiv:2403.19949v1 Announce Type: new
Abstract: Fairness is a critical concern in deep learning, especially in healthcare, where these models influence diagnoses and treatment decisions. Although fairness has been investigated in the vision-only domain, the fairness of medical vision-language (VL) models remains unexplored due to the scarcity of medical VL datasets for studying fairness. To bridge this research gap, we introduce the first fair vision-language medical dataset FairVLMed that provides detailed demographic attributes, ground-truth labels, and clinical notes to facilitate an …

arxiv cs.cv fairness language type vision