ProtoMedAgent uses a privacy-aware agentic workflow with neuro-symbolic bottlenecks to achieve 91.2% faithfulness in clinical report generation, significantly outperforming standard RAG methods on a large patient cohort.
Large language models in radiology reporting-a sys- tematic review of performance, limitations, and clinical im- plications.Intelligence-Based Medicine, page 100287, 2025
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ProtoMedAgent: Multimodal Clinical Interpretability via Privacy-Aware Agentic Workflows
ProtoMedAgent uses a privacy-aware agentic workflow with neuro-symbolic bottlenecks to achieve 91.2% faithfulness in clinical report generation, significantly outperforming standard RAG methods on a large patient cohort.