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

ABSTRACT:

Background

Timely and accurate triage is crucial for the emergency department (ED) care. Recently, there has been growing interest in applying large language models (LLMs) to support triage decision-making. However, most existing studies have evaluated these models using simulated scenarios rather than real-world clinical cases. Therefore, we evaluated the performance of multiple commercial LLMs for non-critical triage support in ED using real-world clinical conversations.

Methods

We retrospectively analyzed real-world triage conversations prospectively collected from three tertiary hospitals in South Korea. Multiple commercial LLMs-including OpenAI GPT-4o, GPT-4.1, O3, Google Gemini 2.0 flash, Gemini 2.5 flash, Gemini 2.5 pro, DeepSeek V3, and DeepSeek R1-were evaluated for

SUBMITTER: Lee S 

PROVIDER: S-EPMC12403343 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature