RadPRISM: Schema-stratified radiology-report supervision for concept-disentangled image representations and visual grounding
Vision-language pretraining learns rich medical image representations from radiology reports, but previous model variants commonly operate within a single shared embedding space, so concept-level structure and interpretability must be recovered post hoc, limiting model transparency and, hence, clinical utility. We intr...