AI RESEARCH
Radiologist-Guided Causal Concept Bottleneck Models for Chest X-Ray Interpretation
arXiv CS.CV
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ArXi:2605.07785v1 Announce Type: new Concept Bottleneck Models (CBMs) in medical imaging aim to improve model interpretability by predicting intermediate clinical concepts before final diagnoses. However, most existing CBMs treat concepts as discriminative predictors of pathology labels, without explicitly modelling the underlying clinical generative process where diseases produce observable radiographic findings. We propose XpertCausal, a radiologist-guided causal CBM for chest X-ray interpretation which models pathology-to-concept relationships using a probabilistic noisy-OR framework.