Answering real-world clinical questions using large language model, retrieval-augmented generation, and agentic systems

By sjmartinez • June 13, 2025

Low YS, Jackson ML, Hyde RJ, Brown RE, Sanghavi NM, Baldwin JD, Pike CW, Muralidharan J, Hui G, Alexander N, Hassan H, Nene RV, Pike M, Pokrzywa CJ, Vedak S, Yan AP, Yao DH, Zipursky AR, Dinh C, Ballentine P, Derieg DC, Polony V, Chawdry RN, Davies J, Hyde BB, Shah NH, Gombar S. Answering real-world clinical questions using large language model, retrieval-augmented generation, and agentic systems. Digit Health. 2025 Jun 9;11:20552076251348850. doi: 10.1177/20552076251348850. PMID: 40510193; PMCID: PMC12159471.

Tags: Artificial intelligence, Cohort study, evidence-based medicine, Fellow, Hematology/Oncology, Large language models, Publications, retrieval-augmented generation

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