基于中医古籍知识构建中医药辨治骨痿的知识图谱

作者：罗作娅，吴筱枫

单位：贵州中医药大学，贵州 贵阳 550000

引用：引用：罗作娅，吴筱枫.基于中医古籍知识构建中医药辨治骨痿的知识图谱[J].中医药导报,2025,31(11):163-168.

DOI：10.13862/j.cn43-1446/r.2025.11.028

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摘要：

目的：运用知识图谱技术，构建基于中医古籍的中医药辨治骨痿的知识图谱，并对辨治骨痿的遣方用药进行归纳总结，以期为中医古籍知识的结构化存储与展示提供思路，为临床辨治骨痿提供数智借鉴。方法：采用Neo4j联合py2neo知识图谱技术，以秦汉至明清时期（1911年以前）中医古籍中骨痿相关知识为数据源构建可视化知识图谱，通过编程实现以关键词的输入调用知识图谱，可视化展示中医药辨治骨痿的过程，在此基础上对辨治骨痿的方、药进行统计分析。结果：使用py2neo库调用Neo4j，从《中华医典》中提取并整理好的结构化数据导入Neo4j，构建了包含2 325个节点和4 644种关系的基于中医古籍知识的中医药辨治骨痿可视化知识图谱，且该知识图谱支持图数据库查询功能。结论：Neo4j联合py2neo数据库的构建能直观地呈现中医古籍中与骨痿相关的古籍、古籍条文、病因病机、方剂、中药之间的关联，通过对中医药辨治骨痿可视化知识图谱的构建，可增强知识关联和提升检索效率，为骨痿相关知识组织和知识服务提供数据支持及方法借鉴，并为骨痿临床遣方用药提供数智支持。

关键词：中医古籍；骨痿；《中华医典》；可视化知识图谱；Neo4j；py2neo库

Abstract：

Objective: To construct a knowledge graph for traditional Chinese medicine (TCM) diagnosis and treatment of Guwei based on ancient Chinese medical books using knowledge graph technology, and to summarize the prescriptions and medicines for diagnosing and treating Guwei. This study aims to provide ideas for the structured storage and display of ancient Chinese medical books ancient Chinese medical books knowledge, as well as digital and intelligent references for the clinical diagnosis and treatment of Guwei. Methods: Neo4j combined with py2neo knowledge mapping technology was used to construct a visual knowledge map by taking the knowledge related to Guwei in the ancient Chinese medical books from the Qin-Han to the Ming-Qing period (before 1911) as the data source, and the knowledge map was invoked with the input of keywords through programming to display the process of treating bone impotence in Chinese medicine visually, and the formulas and medicines used in the treatment of Guwei were statistically analyzed on the basis of the knowledge map. Results: The py2neo library was used to call Neo4j, and the structured data extracted and sorted from Chinese Medical Dictionary was imported into Neo4j. A visualized knowledge graph for TCM diagnosis and treatment of Guwei based on ancient Chinese medical books was constructed, containing 2 325 nodes and 4 644 types of relationships. This knowledge graph supports graph database query functions. Conclusion: The construction of the Neo4j combined with py2neo database can intuitively present the correlations between ancient books, ancient book clauses, etiology and pathogenesis, prescriptions, and Chinese medicines related to Guwei in ancient Chinese medical books. The construction of the visualized knowledge graph for TCM diagnosis and treatment of Guwei can enhance knowledge correlation and improve retrieval efficiency, providing data support and methodological reference for Guwei-related knowledge organization and knowledge services, as well as digital and intelligent support for clinical prescription and medication for Guwei.

Key words：ancient Chinese medical books; Guwei; Chinese Medical Dictionary; visualized knowledge graph; Neo4j; py2neo library

发布时间：2025-11-30

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