让医护人员用自然语言查询患者数据，无需编程即可获取分析结果。
ClinQueryAgent: A Conversational Agent for Population Health Management
- 用对话代理将口语提问转为可执行的数据库查询
- 128名医护人员在15家诊所对14.8万患者数据进行测试
- 适合医疗数据分析员和临床医生快速获取信息
本文介绍ClinQueryAgent，一种用于将自然语言的群体健康问题转化为可执行数据库查询的对话系统。该系统采用具备本地与外部知识库访问权限的智能体架构，在使用强大云上语言模型的同时，确保患者数据不离开安全环境。为缓解长对话中因上下文衰减导致的错误，信息检索由子代理负责。系统通过嵌入现有群体健康管理平台的聊天窗口部署，已由英国国家医疗服务体系（NHS）中15家医疗机构的128名工作人员使用，覆盖148,319名患者。我们在构建的数据集和内部测试阶段评估了系统自主处理多种健康信息任务的能力。结果显示，无论是分析师还是临床医生，均可通过无需编程的自然语言请求，轻松从患者健康记录中生成可操作的信息。系统公开演示链接：https://demo-899965260288.europe-west1.run.app/
原文摘要 · Abstract (English)
In this paper we introduce ClinQueryAgent, a system for translating natural language population health questions into executable database queries using agents with access to both local and external knowledge bases. Our novel architecture enables the use of powerful cloud-based language models whilst ensuring that no patient data leaves the secure environment. To combat inaccuracies over the course of longer dialogues due to context rot, information retrieval is delegated to a sub-agent. We deploy the system via a chat window embedded within an existing population health management platform where it has been used by 128 staff from 15 healthcare practices covering a total of 148,319 patients in the UK's National Health Service (NHS). We evaluate the system's capacity to autonomously handle a range of health informatics tasks on a constructed dataset and via a beta-testing phase. Our results show that both analysts and clinicians are able to easily generate actionable information from patient health records using natural language requests requiring no programming expertise to verify. We make a public demo of the system available at: https://demo-899965260288.europe-west1.run.app/
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