摘要
目的基于Neo4j探究肺癌中医诊疗知识图谱构建。方法收集整理中国知网名老中医治疗肺癌医案的文献,采用自底而上的构建方式,运用BiLSTM-CRF、人工定义规则、内容分析法和Neo4j技术构建肺癌中医诊疗知识图谱。结果共检索376篇名老中医治疗肺癌医案的文献,抽取实体有5901个,定义关系有5种,构建了“病-证-症-方-药”名老中医治疗肺癌医案的知识图谱。结论肺癌中医诊疗知识图谱能够更直观地呈现了肺癌医案中疾病、证候、症状、方剂、中药之间的关联,为深入开展肺癌领域相关研究和实体间潜在的关系发掘奠定一定基础。
Objective To explore the construction of knowledge graph of TCM diagnosis and treatment of lung cancer based on Neo4j.Methods The literature on the treatment of lung cancer by famous veteran teran doctors of TCM in China Knowledge Network was collected and sorted,and the bottom-up construction method was adopted to construct the knowledge graph of lung cancer diagnosis and treatment of Chinese medicine by using BiLSTM-CRF,manual definition rules,content analysis method and Neo4j technology.Results A total of 376 literatures on the treatment of lung cancer by famous veteran teran doctors of TCM were retrieved,5901 entities were extracted,and there were 5 kinds of defined relationships,and knowledge graph of"disease-syndrome-symptom-recipe-drug"of famous veteran teran doctors of TCM in the treatment of lung cancer was constructed.Conclusion The knowledge graph of famous old Chinese medicine treatment of lung cancer can more intuitively present the relationship between diseases,syndromes,symptoms,prescriptions,and traditional Chinese medicines in lung cancer medical records,and lay a certain foundation for in-depth research on lung cancer and potential relationships between entities.
作者
徐安迎
胡孔法
杨涛
Xu Anying;Hu Kongfa;Yang Tao(School of Artificial Intelligence and Information Technology,Nanjing University of Chinese Medicine,Nanjing 210023,China;Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine in Prevention and Treatment of Tumor,Nanjing 210013,China)
出处
《世界科学技术-中医药现代化》
CSCD
北大核心
2023年第4期1456-1461,共6页
Modernization of Traditional Chinese Medicine and Materia Medica-World Science and Technology
基金
国家自然科学基金委员会面上项目(82074580):基于知识图谱的现代名老中医诊治肺癌用药规律及其机制研究,负责人:胡孔法
关键词
Neo4j
肺癌
知识图谱
名老中医
Neo4j
Lung cancer
Knowledge graph
Prestigious Chinese physician
作者简介
通讯作者:胡孔法,教授,博士生导师,主要研究方向:物联网与云计算、中医药人工智能与大数据分析研究。
