AgentMD:通过大规模的临床工具学习,赋予语言代理人风险预测的权力
Qiao Jin1, Zhizheng Wang1, Yifan Yang1,2
1Division of Intramural Research (DIR), National Library of Medicine (NLM), National Institutes of Health (NIH), Bethesda, MD, USA.
Nature communications
|October 23, 2025
概括
AgentMD,一种新的语言代理,有效地策划和使用临床计算器. 与现有模型相比,它显著提高了医疗风险预测的准确性,有助于个人患者护理和医疗分析.
科学领域:
- 人工智能在医学中的应用
- 临床信息学 临床信息学
- 医疗保健分析 医疗保健分析
背景情况:
- 临床计算器是必不可少的,但面临的可用性和访问性挑战.
- 目前的工具缺乏自动化策划和应用功能.
- 需要先进的人工智能来弥合临床决策支持方面的差距.
研究的目的:
- 推出AgentMD,一种用于策划和应用临床计算器的语言代理.
- 评估AgentMD在临床风险预测和医疗保健分析方面的表现.
- 展示语言代理在增强临床工作流程方面的潜力.
主要方法:
- 代理MD利用PubMed策划了2,164个可执行的临床计算器,具有很高的准确性.
- 质量检查和单元测试确保了计算器的可靠性.
- AgentMD被评为自主计算器选择和应用的工具用户.
主要成果:
- 与GPT-4 (40.9%) 相比,AgentMD在风险预测方面表现出更高的准确性 (87.7%).
- 精确的个人级别的医疗风险计算在698个急诊室笔记中得到了确认.
- AgentMD为机构风险管理提供了人口层面的见解.
结论:
- 像AgentMD这样的语言代理可以有效地策划和利用临床计算器.
- AgentMD为个体患者的风险评估提供了显著的改进.
- AgentMD支持大规模的医疗分析和机构风险管理.
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