Performance of ChatGPT, Gemini and DeepSeek for non-critical triage support using real-world conversations in emergency department
LLMs can accurately triage ED patient urgency using real-world clinical conversations. Several models demonstrated both high sensitivity and acceptable response times, supporting the feasibility of LLM in non-critical triage support tools in diverse clinical environments. These findings apply to non-critical patients (KTAS 3-5), and further research should address integration with objective clinical data and real-time workflow.
Authors
- Sung Woo Moon (ORCID: https://orcid.org/0000-0001-9917-9802)
- Hanjin Cho
- Jong-Hak Park (ORCID: https://orcid.org/0000-0001-9481-6358)
- Sukyo Lee (ORCID: https://orcid.org/0000-0002-7105-1951)
- Sejoong Ahn (ORCID: https://orcid.org/0000-0002-6003-2552)
- Sumin Jung (ORCID: https://orcid.org/0009-0009-7663-170X)
Institutions
- Ansan University (KR)
Publication Details
- Journal
- BMC Emergency Medicine
- Published
- 2025-09-01
- DOI
- https://doi.org/10.1186/s12873-025-01337-2
- Citations
- 12
- Primary Topic
- Emergency and Acute Care Studies
- Type
- article
- Field-Weighted Citation Impact
- 27.04