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.

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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
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article

Performance of ChatGPT, Gemini and DeepSeek for non-critical triage support using real-world conversations in emergency department

Sung Woo Moon, Hanjin Cho, Jong-Hak Park, Sukyo Lee et al.
12 citations
BMC Emergency Medicine
Emergency and Acute Care Studies
27.04
article

Performance of ChatGPT, Gemini and DeepSeek for non-critical triage support using real-world conversations in emergency department

Sung Woo Moon, Hanjin Cho, Jong-Hak Park, Sukyo Lee, Sejoong Ahn, Sumin Jung
article en
12 citations

Abstract

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.

BMC Emergency MedicineVol. 25(1)
Ansan University (KR)
Openalex Percentile: Top 0%
Emergency and Acute Care Studies
27.04
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