分类体系完善、药品信息全面的药品知识库能够为临床决策以及临床合理用药提供依据和支持。该文以国内的多个医药资源作为参考和数据来源,建立了药品库知识描述体系和分类体系,对药品进行标准化分类并形成详细的知识描述,构建了多来源的中文药品知识库(Chinese Medicine Knowledge Base,CMKB)。所构建的CMKB的分类包括27种一级类别和119种二级类别,从药品的适应证、用法用量等多个层面对14 141种药品进行描述并采用BiLSTM-CRF和T-BiLSTM-CRF模型将非结构化描述中的疾病实体进行了信息抽取,形成了对药品属性的结构化信息抽取,建立了药品实体与自动抽取的疾病实体之间的知识关联。所构建的CMKB能够与中文医学知识图谱进行连接,扩充药品信息,并能够为智能诊断和医疗问答等提供知识基础。
Abstract
A medicine knowledge base with complete classification system and comprehensive drug information can provide basis and support for clinical decision-making and rational drug use. Based on multiple domestic medical resources as references and data sources, this paper establishes the knowledge description system and classification system of medicine base, standardizes classification of drugs and forms detailed knowledge description, and constructs a multi-source Chinese Medicine Knowledge Base (CMKB). The classification of CMKB includes 27 first-level categories and 119 secondary categories, and describes 14,141 drugs from multiple levels such as drug indications, dosage and administration. Furthermore, the BiLSTM-CRF and T-BiLSTM-CRF models are used to extract information of disease entities in unstructured descriptions, forming structured information extraction of drug attributes, and establishing the knowledge association between drug entities and automatically extracted disease entities. The constructed CMKB can be connected with the Chinese medical knowledge graph to expand drug information, and can provide the knowledge basis for intelligent diagnosis and medical question and answer.
关键词
中文药品知识库 /
知识关联 /
命名实体识别
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Key words
Chinese medicine knowledge base /
knowledge association /
named entity recognition
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参考文献
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脚注
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基金
国家重点研发计划(2017YFB1002101);国家社会科学基金(17ZDA138);中国博士后科学基金(2019TQ0286);河南省科技攻关项目(192102210260);河南省医学科技攻关计划省部共建项目(SB201901021);河南省高等学校重点科研项目(19A520003,20A520038);教育部人文社科规划项目(20YJA740033);河南省哲学社会科学规划项目 (2019BYY016)
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