Shun-Ting Chang

UNCOVERING OVERCONFIDENT FAILURES IN CXR MODELS VIA AUGMENTATION-SENSITIVITY RISK SCORING

Deep learning models achieve strong performance in chest radiograph (CXR) interpretation, yet fairness and reliability concerns persist. Models often show uneven accuracy across patient subgroups, leading to hidden failures not reflected in aggregate metrics. Existing error detection approaches -- b…