2 papers
cs.CV2026
A data- and compute-efficient chest X-ray foundation model beyond aggressive scaling
Chong Wang, Yabin Zhang, Yunhe Gao +9
Foundation models for medical imaging are typically pretrained on increasingly large datasets, following a "scale-at-all-costs" paradigm. However, this strategy faces two critical…
cs.CV2025
From Detection to Mitigation: Addressing Bias in Deep Learning Models for Chest X-Ray Diagnosis
Clemence Mottez, Louisa Fay, Maya Varma +2
Deep learning models have shown promise in improving diagnostic accuracy from chest X-rays, but they also risk perpetuating healthcare disparities when performance varies across de…