Intersectional fairness in vision-language models for medical image disease classification
Published in npj Digital Medicine, 2026
Cross-Modal Alignment Consistency (CMAC-MMD), a training framework that standardises diagnostic certainty across intersectional patient subgroups without requiring sensitive demographic data at inference, reducing missed-diagnosis gaps while improving AUC on dermatology and glaucoma cohorts.
Recommended citation: Yupeng Zhang, Adam G. Dunn, Usman Naseem, Jinman Kim. (2026). "Intersectional fairness in vision-language models for medical image disease classification." npj Digital Medicine. doi:10.1038/s41746-026-03030-5 https://www.nature.com/articles/s41746-026-03030-5
