Effectiveness of a large language model for clinical information retrieval regarding shoulder arthroplasty

Effectiveness of a large language model for clinical information retrieval regarding shoulder arthroplasty

Abstract Purpose To determine the scope and accuracy of medical information provided by ChatGPT‐4 in response to clinical queries concerning total shoulder arthroplasty (TSA), and to compare these results to those of the Google search engine. Methods A patient‐replicated query for ‘total shoulder re...

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Bibliographic Details
Main Authors: Jacob F. Oeding, Amy Z. Lu, Michael Mazzucco, Michael C. Fu, David M. Dines, Russell F. Warren, Lawrence V. Gulotta, Joshua S. Dines, Kyle N. Kunze
Format: Article
Language:English
Published: Wiley 2024-10-01
Series:Journal of Experimental Orthopaedics
Subjects:
ChatGPT
information retrieval
large language model
LLM
total shoulder arthroplasty
Online Access:https://doi.org/10.1002/jeo2.70114
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https://doi.org/10.1002/jeo2.70114

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