基于命名实体识别与Neo4j的中文电子病历知识图谱构建和应用 |
修订日期:2022-10-07 点此下载全文 |
引用本文:许思特,孙木.基于命名实体识别与Neo4j的中文电子病历知识图谱构建和应用[J].医学信息学杂志,2022,43(12):50-56 |
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中文摘要:基于真实中文电子病历与网络爬取数据,构建病历实体识别模型,确定实体关系,进行知识图谱可视化展现,搭建基于规则匹配的问答系统。探索适用于中文电子病历的知识图谱与知识体系构建方法,提高医院统计部门相关审核工作效率,为人工智能技术在医疗卫生行业应用奠定基础。 |
中文关键词:中文电子病历 RoBERTa 命名实体识别 知识图谱 Neo4j |
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Construction and Application of Knowledge Graph in Chinese Electronic Medical Records Based on Name Entity Recognition and Neo4j |
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Abstract:Based on actual Chinese electronic medical records and web crawling data,the paper constructs an entity recognition model of medical records,determines entity relationships,presents the visualization of knowledge graph,builds a question and answer system based on rule matching. It explores the construction method of knowledge graph and knowledge system applicable to Chinese electronic medical records, improves the work efficiency of hospital statistics department related audit, and lays a foundation for the application of artificial intelligence technology in the medical and health industry. |
keywords:Chinese electronic medical records RoBERTa name entity recognition knowledge graph Neo4j |
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