Evaluating GPT-4o for emergency disposition of complex respiratory cases with pulmonology consultation: a diagnostic accuracy study
GPT-4o demonstrated high sensitivity in identifying ED patients requiring hospital admission, particularly those needing intensive care, when provided with progressively enriched clinical input. However, its low sensitivity for discharge prediction resulted in frequent overtriage, limiting its utility for autonomous decision-making. This proof-of-concept study demonstrates GPT-4o's capacity to stratify disposition decisions in complex respiratory cases under varying levels of limited input data. However, these findings should be interpreted in light of key limitations, including the selective high-acuity cohort and the absence of vital signs, and require prospective validation before clinical implementation.
Authors
- Ertuğ Günsoy (ORCID: https://orcid.org/0000-0002-9653-3236)
- Canan Yıldırım (ORCID: https://orcid.org/0009-0004-5359-6335)
- Mehmet Veysel Öncül (ORCID: https://orcid.org/0000-0002-3865-8364)
- Ahmet Aykut (ORCID: https://orcid.org/0009-0001-3173-8994)
Institutions
- Education Training And Research (US)
Publication Details
- Journal
- Scandinavian Journal of Trauma Resuscitation and Emergency Medicine
- Published
- 2025-10-02
- DOI
- https://doi.org/10.1186/s13049-025-01475-3
- Citations
- 2
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 1.31