Evaluating ChatGPT, Gemini and other Large Language Models (LLMs) in orthopaedic diagnostics: A prospective clinical study
GPT-4o demonstrated high accuracy and consistency in diagnosing OA based solely on patient-reported questionnaires, underscoring its potential as a supplementary diagnostic tool in clinical settings. Nevertheless, the reliance on patient-reported data without direct physician involvement highlights the critical need for medical oversight to ensure diagnostic accuracy. Further research is needed to refine LLM capabilities and expand their utility in broader diagnostic applications.
Authors
- Michael Schuster (ORCID: https://orcid.org/0000-0003-2975-8969)
- Katrin Michalk
- Tobias Renkawitz
- Loreto Pulido Quintana (ORCID: https://orcid.org/0000-0002-3600-1887)
- Stefano Pagano (ORCID: https://orcid.org/0009-0006-6721-7564)
- Günther Maderbacher
- Julia Sabrina Schiegl
- Jan Reinhard (ORCID: https://orcid.org/0000-0003-2946-2535)
- Luigi Strumolo
Institutions
- Asklepios Kliniken Bad Abbach (DE)
- Agaplesion Markus Hospital (DE)
- Data Management (Italy) (IT)
Publication Details
- Journal
- Computational and Structural Biotechnology Journal
- Published
- 2024-12-26
- DOI
- https://doi.org/10.1016/j.csbj.2024.12.013
- Citations
- 21
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 2.53