Comparitive performance of artificial intelligence-based large language models on the orthopedic in-training examination.

Journal: Journal of orthopaedic surgery (Hong Kong)
PMID: 40028745

Abstract

BACKGROUND: Large language models (LLMs) have many clinical applications. However, the comparative performance of different LLMs on orthopedic board style questions remains largely unknown.

Authors

  • Andrew Y Xu
    Warren Alpert Medical School, Brown University, Providence, RI, USA.
  • Manjot Singh
    Warren Alpert Medical School, Brown University, Providence, RI, USA.
  • Mariah Balmaceno-Criss
    Warren Alpert Medical School, Brown University, Providence, RI, USA.
  • Allison Oh
    Harvard College, Harvard University, Cambridge, MA, USA.
  • David Leigh
    Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA.
  • Mohammad Daher
    Department of Orthopedic Surgery, The Warren Alpert Medical School, Brown University, Providence, RI 02912, USA.
  • Daniel Alsoof
    Department of Orthopedic Surgery, Warren Alpert Medical School of Brown University, Providence, Rhode Island.
  • Christopher L McDonald
    Department of Orthopedic Surgery, Warren Alpert Medical School of Brown University, Rhode Island Hospital, Providence, Rhode Island, USA.
  • Bassel G Diebo
    Department of Orthopedics, Warren Alpert Medical School, Brown University, Providence, RI, USA.
  • Alan H Daniels
    1Division of Spine Surgery and.

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