中华中医药学刊2026，Vol.44Issue(1)：1-6,后插1-后插5,11.DOI:10.13193/j.issn.1673-7717.2026.01.001
基于ChatGLM的中医妇科知识图谱自动化构建与临床决策支持研究
Research on Automated Construction and Clinical Decision Support of Traditional Chinese Medicine Gynecology Knowledge Graphs Based on ChatGLM
摘要
Abstract
The study aims to construct a knowledge graph for traditional Chinese medicine(TCM)gynecology based on large language models.The goal is to systematically organize and present the complex knowledge system of this field,revealing the in-trinsic connections and evolution patterns among diseases,thereby enhancing the precision of clinical decision-making.The study selected 349 TCM gynecology papers from China National Knowledge Infrastructure(CNKI).ChatGLM was used with multi-round prompt templates to achieve zero-shot entity relationship extraction.Evaluation metrics were designed to objective-ly assess the extraction results.Efficient processing was achieved through API interfaces interacting with the model.The Neo4j graph database was used to construct and visualize the knowledge graph.The study shows that ChatGLM performs better in knowledge extraction compared to traditional Bi-LSTM-CRF models,significantly improving precision,recall and F1 scores.The constructed knowledge graph effectively supports the clinical decision-making in TCM gynecology,enhancing the diagnostic efficiency and accuracy and demonstrating the practical value.关键词
大语言模型/中医妇科/知识图谱/知识抽取/Neo4j/Bi-LSTM-CRFKey words
large language model/TCM gynecology/knowledge graph/knowledge extraction/Neo4j/Bi-LSTM-CRF分类
医药卫生引用本文复制引用
汤少梁,龙秋予,李君妍,申俊龙,赵楠..基于ChatGLM的中医妇科知识图谱自动化构建与临床决策支持研究[J].中华中医药学刊,2026,44(1):1-6,后插1-后插5,11.基金项目
国家社会科学基金重点项目(19AZD018) （19AZD018）
江苏智慧中医药健康服务工程研究中心开放课题项目(ZHZYY202402) （ZHZYY202402）
