计算机工程与应用2026，Vol.62Issue(9)：133-144,12.DOI:10.3778/j.issn.1002-8331.2504-0243
一种面向中医问诊的数据知识双驱动大模型
Data-Knowledge Dual-Driven Large Model for Chinese Medicine Consultation
摘要
Abstract
Generalized large language models(LLMs)in the field of Chinese medicine consultation suffer from the problems of insufficient knowledge retrieval ability and low query analysis accuracy,which affect their accuracy and reliability.Therefore,this study proposes a data-knowledge dual-driven large language model for TCM consultation(DualKAG-ShenNong).DualKAG-ShenNong adopts a medical-style fine-tuning strategy,which introduces an external knowledge base during fine-tuning,to make up for the limitations of data-driven models in terms of knowledge utilization.At the same time,it combines the knowledge graph(KG)-based retrieval augmented generation(RAG)technology to provide inference chains with TCM theoretical knowledge and design prompt templates,which fully utilizes the powerful genera-tive and inference capabilities of the LLM to provide users with accurate TCM consultation services.A large number of experimental results show that DualKAG-ShenNong outperforms the traditional model in a number of metrics such as ROUGE,BLEU,etc.,which verifies its effectiveness and scientificity in Chinese medicine intelligent Q&A,and provides a solid application support.关键词
数据-知识双驱动/DualKAG-ShenNong/Medical式微调技术/外部知识库Key words
dual data-knowledge driver/DualKAG-ShenNong/Medical-style fine-tuning technique/external knowledge base分类
信息技术与安全科学引用本文复制引用
范越,杜建强,罗计根,黄强,贺佳,廖明..一种面向中医问诊的数据知识双驱动大模型[J].计算机工程与应用,2026,62(9):133-144,12.基金项目
国家自然科学基金(82260988,82274680,82160955) （82260988,82274680,82160955）
江西省研究生创新专项基金(YC2024-S722) （YC2024-S722）
江西中医药大学校级科技创新团队发展项目(CXTD22015) （CXTD22015）
江西省中医药管理局科技计划项目(2024B0736). （2024B0736）
