Representation Disentanglement for Fair Chest X-Ray Diagnosis

Excerpt

arXiv:2610.06041v1 Announce Type: cross Abstract: Deep learning has advanced chest X-ray (CXR) diagnosis, yet demographic biases in learned representations may contribute to performance disparities across intersectional groups. We propose a single-encoder framework combining dual-level decorrelation with prototype-guided cross-group contrastive learning to reduce demographic dependence while accounting for within-class variation. We further propose Demographic Representation Alignment Reduction