ChatGPT4’s diagnostic accuracy in inpatient neurology: A retrospective cohort study
Our findings suggest that CG4 can serve as a valuable diagnostic tool within the domain of inpatient neurology, providing comprehensive and accurate initial diagnoses comparable to those of consultant neurologists. The use of CG4 might contribute to better patient outcomes by serving as an aid in diagnosis and treatment recommendations, potentially leading to reduced missed diagnoses and quicker diagnostic processes. Continuous strategies and evaluations to improve LLMs' accuracy remain crucial. Further studies with larger sample sizes and independent third-party evaluations are recommended to confirm these findings and assess the impact of LLMs on patient health.
Authors
- Michael Neeki (ORCID: https://orcid.org/0000-0003-0050-0788)
- Joseph Dhahbi (ORCID: https://orcid.org/0000-0001-5832-3804)
- Leo Issagholian (ORCID: https://orcid.org/0009-0007-8522-1898)
- Sebastian Cano-Besquet
- Tyler Rice-Canetto
- Hadi Abou-El-Hassan
- Simon Alarcon
- Jason Zimmerman
- Nasser Salomon
- Ivan Rojas
Institutions
- Arrowhead Regional Medical Center (US)
- University of California System (US)
Publication Details
- Journal
- Heliyon
- Published
- 2024-12-01
- DOI
- https://doi.org/10.1016/j.heliyon.2024.e40964
- Citations
- 5
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.60