慢性病智能医疗问答系统构建与评价：一种基于<bold>GraphRAG</bold>与<bold>MoE</bold>的混合建模方法

doi:10.3772/j.issn.1000-0135.2026.03.010

情报学报

2026, Vol. 45

Issue (3): 447-462 DOI: 10.3772/j.issn.1000-0135.2026.03.010

情报技术与应用

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慢性病智能医疗问答系统构建与评价：一种基于GraphRAG与MoE的混合建模方法

马鑫^1,2,4, 王芳^1,2,3, 张峰⁴, 李照川⁴

1.南开大学信息与传播学院信息资源管理系，天津 300071
2.南开大学网络社会治理研究中心，天津 300071
3.南开大学图书馆，天津 300071
4.浪潮软件科技有限公司，济南 250000

Construction and Evaluation of Intelligent Medical Q&A System for Chronic Diseases: A Hybrid Modeling Approach Based on GraphRAG and MoE

Ma Xin^1,2,4, Wang Fang^1,2,3, Zhang Feng⁴, Li Zhaochuan⁴

1.Department of Information Resources Management, School of Information and Communication, Nankai University, Tianjin 300071
2.Center for Network Society Governance, Nankai University, Tianjin 300071
3.Nankai University Library, Tianjin 300071
4.Inspur Software Technology Co., Ltd., Jinan 250000

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摘要随着慢性病成为全球公共卫生领域的核心挑战，患者对高质量、个性化、可持续的健康信息服务需求日益增长。近年来，尽管大语言模型在医疗问答任务中展现出显著优势，但现有系统在面对慢性病管理这一长期性、情境化、语义复杂的场景时，仍面临知识调度粒度粗、语义感知能力弱与模型响应一致性差等瓶颈。为此，本研究遵循“结构化知识建模—混合驱动检索—大模型协同应答”三阶段流程，提出一种融合图检索增强生成（graph retrieval-augmented generation，GraphRAG）与混合专家网络（mixture of experts，MoE）的慢性病问答系统。首先，构建覆盖疾病演化、生活方式干预和长期管理要素的多源异构专有知识图谱，通过结合关键词匹配、语义向量召回与多子图提示融合的三通道混合图谱检索机制，实现对复杂信息需求的动态知识调度；其次，初筛用户查询合法性与规范性，结合用户隐含意图与融合子图，通过MoE动态门控智能体对9种开源大模型进行指令级协同，实现语义深度与生成精度的双擎增强；最后，引入常识校验、内容完整性检查与格式化规则，精细预生成文本，确保输出结果的准确性、完整性与语言可读性。本研究自建覆盖118种慢性病与3类管理任务的测试集CdMedQA，综合采用客观指标评价和主观满意度对比两种方式验证系统性能。结果表明，本研究构建系统在准确性、清晰度、个性化及情境适应性等方面显著优于多种通用与医疗垂直大模型基线。研究结果不仅为慢性病智能化管理提供了新路径，也为多源知识驱动下人机交互优化与生成内容可信性提升提供了理论支持与技术方案。

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	马鑫
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关键词 ：慢性病支持, 医疗问答系统, 混合专家网络, 图检索增强生成, 大语言模型

收稿日期: 2025-06-01

基金资助:文化和旅游部部级社科研究项目“文化和旅游数据资源开发利用模式研究”（25DY09）；南开大学亚洲研究中心项目“数智赋能基层社会风险预警与治理研究”（AS2508）。

作者简介: 马鑫，1995年生，博士，主要研究方向为推荐系统、人机协同、大模型与健康信息学；王芳，通信作者，1970年生，教授，博士生导师，主要研究方向为知识发现、情感挖掘、政府信息资源管理与电子政务，E-mail：wangfangnk@nankai.edu.cn；张峰，1975年生，正高级工程师，主要研究方向为数据共享开放、一体化政务大数据体系、数字政府等；李照川，1984年生，正高级工程师，主要研究方向为一体化政务大数据体系、知识图谱、隐私计算、社会治理等；

引用本文:

马鑫, 王芳, 张峰, 李照川. 慢性病智能医疗问答系统构建与评价：一种基于GraphRAG与MoE的混合建模方法[J]. 情报学报, 2026, 45(3): 447-462.
Ma Xin, Wang Fang, Zhang Feng, Li Zhaochuan. Construction and Evaluation of Intelligent Medical Q&A System for Chronic Diseases: A Hybrid Modeling Approach Based on GraphRAG and MoE. 情报学报, 2026, 45(3): 447-462.

链接本文:

https://qbxb.istic.ac.cn/CN/10.3772/j.issn.1000-0135.2026.03.010 或 https://qbxb.istic.ac.cn/CN/Y2026/V45/I3/447

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