大型语言模型在儿科急诊室的诊断效果:一个试点研究
Francesco Del Monte1, Roberta Barolo2, Maria Circhetta3
1Department of Pediatric Emergency, Regina Margherita Children's Hospital-A.O.U. Città Della Salute e Della Scienza di Torino, Turin, Italy.
Frontiers in digital health
|July 16, 2025
概括
大型语言模型 (LLM) 在儿科紧急诊断方面表现有前途. 聊天GPT-4o在准确性方面表现优于医生,这表明AI可以帮助临床决策.
科学领域:
- 人工智能在医学中的应用
- 临床决策支持系统 临床决策支持系统
- 儿科急救医学 儿科急救医学
背景情况:
- 儿科急诊室 (PED) 面临着大量患者和复杂的诊断挑战.
- 大型语言模型 (LLM) 提供了增强患者护理的潜力.
- 目前正在研究LLM在支持PED临床推理和诊断方面的有效性.
研究的目的:
- 在现实的PED场景中评估基于LLM的聊天机器人的诊断性能.
- 评估LLM作为儿童紧急病例的潜在诊断助手.
- 为了比较LLM诊断准确度与医生在第三级护理环境.
主要方法:
- 测试了五个LLM (ChatGPT-4o,双子1.5 Pro,双子1.5 Flash,Llama-3-8B,ChatGPT-4o mini) 的使用情况.
- 法学士和23名医生 (PED医生,PED住院医生,EM住院医生) 诊断了80例儿科病例.
- 回答与最终诊断进行了比较,在五级准确度尺度上进行专家评估.
主要成果:
- 聊天GPT-4o获得最高分数 (72.5),超过了PED医生 (61.88,p<0.05).
- 双子1.5 Pro也表现出强的表现 (62.75).
- 随着案件的复杂性,LLM的表现下降,但ChatGPT-4o在困难的案件中保持了准确性.
结论:
- 像ChatGPT-4o和Gemini 1.5 Pro这样的高级LLM可以成为急诊室医生的宝贵工具.
- 人工智能聊天机器人可以支持临床决策,而不会取代医生的判断.
- 开发共享的协议,以便在医疗保健中有效的AI-医生合作是必不可少的.
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