| 引用本文: | 何霆,吴雅婷,王华珍,熊英杰,孙偲,徐汉川.基于EHR的医疗知识图谱研究与应用综述[J].哈尔滨工业大学学报,2018,50(11):137.DOI:10.11918/j.issn.0367-6234.201806001 |
| HE Ting,WU Yating,WANG Huazhen,XIONG Yingjie,SUN Cai,XU Hanchuan.A survey of medical knowledge graph based on EHR[J].Journal of Harbin Institute of Technology,2018,50(11):137.DOI:10.11918/j.issn.0367-6234.201806001 |
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| 摘要: |
| 电子健康记录(EHR)作为一种医疗信息化手段，在数十年的使用过程中储存和积累了越来越多的医疗过程和结果大数据.知识图谱作为一种从海量数据中抽取结构化知识的手段，近年来在多个行业展示了广阔的应用前景.知识图谱的优势在于对海量、异构的数据进行组织，完成知识推理.知识图谱适用于自然语言的分析，有助于在以自然语言形式存在的海量EHR数据中获得宝贵的医疗知识和医疗经验. EHR分析研究的价值主要集中在辅助诊断、辅助治疗和疾病预测.利用大量的EHR数据构建医疗知识图谱，当新的患者数据来临之时，知识图谱可以发挥查询扩展、临床决策支持和疾病预测等作用.本文首先简要介绍了EHR的发展现状，以及现有著名的EHR数据集及其应用成果.其次，在概括介绍知识图谱发展总体现状基础上，分析了知识图谱在医疗领域的发展趋势和热点迁移.然后，对基于EHR的医疗知识图谱研究与应用进展进行了比较全面的总结，包括EHR的信息抽取、数据整合、查询扩展、临床决策支持和疾病预测等.最后，对该领域未来发展方向和面临的挑战作了展望.
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| 关键词: EHR 知识图谱 医疗知识图谱 研究和应用进展 |
| DOI：10.11918/j.issn.0367-6234.201806001 |
| 分类号:TP182 |
| 文献标识码:A |
| 基金项目:国家自然科学基金(71571056)；华侨大学科研启动基金(16BS304) |
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| A survey of medical knowledge graph based on EHR |
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HE Ting1,WU Yating1,WANG Huazhen1,XIONG Yingjie1,SUN Cai1,XU Hanchuan2
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(1.School of Computer Science and Technology, Huaqiao University, Xiamen 361021, China; 2.School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China)
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| Abstract: |
| Electronic health record (EHR) as a means of medical informatization has stored and accumulated big data of medical processes and results. Knowledge graph as a means to extract structured knowledge from massive data has recently shown broad application prospects in many industries. The application of knowledge graph technology to the analysis of EHR data can help obtain valuable medical knowledge and experience which could be used to improve the effectiveness and efficiency of medical industry significantly. This paper firstly introduced the development status of EHR, the existing famous EHR data sets and their application results. Secondly, on the basis of summarizing the current developments of knowledge graph, it analyzed the trend and hot-spot migration of knowledge graph in medical field as well. Then, it summarized the research and application progresses of EHR based medical knowledge graph which include the information extraction, data integration, query expansion, clinical diagnostic support and disease prediction of EHR, etc. Finally, this paper also gave the future development directions and challenges of EHR based medical knowledge graph.
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| Key words: EHR knowledge graph medical knowledge graph advances in research and application |
