Who Gets Missed in the Tail? Thresholded Subgroup Underdiagnosis in Long-Tailed Chest X-ray Classification
Researchers analyze how thresholding in long-tailed chest X-ray classification models leads to underdiagnosis of rare-positive patients within specific subgroups.
The study investigates the fairness implications of converting continuous model scores into binary decisions in multi-label chest X-ray classification. By applying a diagnostic ladder to datasets like VinDr-CXR and MIMIC-CXR, the authors demonstrate that even models with strong ranking performance can systematically miss rare-positive cases when thresholds are applied, particularly across demographic or clinical sub…
