Bin Sheng

Retrieval-Augmented Generation in Radiology: A Scoping Review of Architectures, Imaging Applications, and Directions for Equitable Deployment.

Overall, while RAG shows promise for improving factual grounding in radiology AI, current evaluation paradigms likely overestimate real-world clinical readiness and future work should prioritize retrieval quality, clinically grounded evaluation, safety-critical error analysis, bias assessment, and deployment-relevant efficiency metrics to enable responsible clinical translation.