MedBridge adapts pretrained VLMs to multi-label medical diagnosis via query tokens for non-destructive alignment and expert routing, reporting 6-15% AUC gains on chest radiograph benchmarks across eight models.
Expert-level detection of pathologies from unannotated chest x-ray images via self- supervised learning.Nature biomedical engineering, 6(12): 1399–1406, 2022
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Adapting Foundation Vision-Language Models to Medical Diagnosis via Query-Driven Expert Bridging
MedBridge adapts pretrained VLMs to multi-label medical diagnosis via query tokens for non-destructive alignment and expert routing, reporting 6-15% AUC gains on chest radiograph benchmarks across eight models.