TY - JOUR
T1 - Large language models in medicine
T2 - A review of current clinical trials across healthcare applications
AU - Omar, Mahmud
AU - Nadkarni, Girish N.
AU - Klang, Eyal
AU - Glicksberg, Benjamin S.
N1 - Publisher Copyright:
© 2024 Omar et al.
PY - 2024/11
Y1 - 2024/11
N2 - This review analyzes current clinical trials investigating large language models' (LLMs) applications in healthcare. We identified 27 trials (5 published and 22 ongoing) across 4 main clinical applications: patient care, data handling, decision support, and research assistance. Our analysis reveals diverse LLM uses, from clinical documentation to medical decision- making. Published trials show promise but highlight accuracy concerns. Ongoing studies explore novel applications like patient education and informed consent. Most trials occur in the United States of America and China. We discuss the challenges of evaluating rapidly evolving LLMs through clinical trials and identify gaps in current research. This review aims to inform future studies and guide the integration of LLMs into clinical practice.
AB - This review analyzes current clinical trials investigating large language models' (LLMs) applications in healthcare. We identified 27 trials (5 published and 22 ongoing) across 4 main clinical applications: patient care, data handling, decision support, and research assistance. Our analysis reveals diverse LLM uses, from clinical documentation to medical decision- making. Published trials show promise but highlight accuracy concerns. Ongoing studies explore novel applications like patient education and informed consent. Most trials occur in the United States of America and China. We discuss the challenges of evaluating rapidly evolving LLMs through clinical trials and identify gaps in current research. This review aims to inform future studies and guide the integration of LLMs into clinical practice.
UR - https://www.scopus.com/pages/publications/85210305745
U2 - 10.1371/journal.pdig.0000662
DO - 10.1371/journal.pdig.0000662
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C2 - 39561120
AN - SCOPUS:85210305745
SN - 2767-3170
VL - 3
JO - PLOS Digital Health
JF - PLOS Digital Health
IS - 11 November
M1 - e0000662
ER -