从被动到主动：一种用于自动化医疗预咨询的分层多智能体框架
From Passive to Proactive: A Hierarchical Multi-Agent Framework for Automated Medical Pre-Consultation
AI总结：
本文提出了一种分层多智能体框架，用于解决医疗分诊中的分类准确性、部门异质性和提问效率问题，通过三个智能体协作实现高效准确的患者分诊。
摘要：
疫情后医疗需求的激增，加上关键护理人员的短缺，给医疗分诊系统带来了前所未有的压力，需要创新的AI驱动解决方案。我们提出了一种用于医疗分诊的多智能体交互智能系统，该系统解决了当前基于AI的分诊系统中的三个基本挑战：医疗专业不足导致的误分类、医疗机构中部门结构的异质性，以及效率低下且阻碍快速分诊决策的细节导向提问。我们的系统采用三个专门的智能体--RecipientAgent、InquirerAgent和DepartmentAgent--通过Inquiry Guidance机制和Classification Guidance机制协作，将无结构的患者症状转化为准确的部门推荐。为了确保稳健评估，我们从
英文摘要：
The post-pandemic surge in healthcare demand, coupled with critical nursing shortages, has placed unprecedented pressure on medical triage systems, necessitating innovative AI-driven solutions. We present a multi-agent interactive intelligent system for medical triage that addresses three fundamental challenges in current AI-based triage systems: inadequate medical specialization leading to misclassification, heterogeneous department structures across healthcare institutions, and inefficient detail-oriented questioning that impedes rapid triage decisions. Our system employs three specialized agents--RecipientAgent, InquirerAgent, and DepartmentAgent--that collaborate through Inquiry Guidance mechanism and Classification Guidance Mechanism to transform unstructured patient symptoms into accurate department recommendations. To ensure robust evaluation, we constructed a comprehensive Chinese medical triage dataset from "Ai Ai Yi Medical Network", comprising 3,360 real-world cases spanning 9 primary departments and 62 secondary departments. Experimental results demonstrate that our multi-agent system achieves 89.6% accuracy in primary department classification and 74.3% accuracy in secondary department classification after four rounds of patient interaction. The system's dynamic matching based guidance mechanisms enable efficient adaptation to diverse hospital configurations while maintaining high triage accuracy. We successfully developed this multi-agent triage system that not only adapts to organizational heterogeneity across healthcare institutions but also ensures clinically sound decision-making.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
