Vision-Language Models Encode Clinical Guidelines for Concept-Based Medical Reasoning

ArXi:2603.08921v1 Announce Type: cross Concept Bottleneck Models (CBMs) are a prominent framework for interpretable AI that map learned visual features to a set of meaningful concepts for task-specific downstream predictions. Their sequential structure enhances transparency by connecting model predictions to the underlying concepts that them. In medical imaging, where transparency is essential, CBMs offer an appealing foundation for explainable model design.