Institute of Information on Traditional Chinese Medicine, China Academy of Chinese Medical Science, Beijing 100700, China.
National Data Center of Traditional Chinese Medicine, China Academy of Chinese Medical, China.
Biomed Res Int. 2022 Feb 14;2022:7139904. doi: 10.1155/2022/7139904. eCollection 2022.
This article uses the real medical records and web pages of Chinese medicine diagnosis and treatment of hepatitis B to extract structured medical knowledge, and obtains a total of 8,563 entities, 96,896 relationships, 32 entity types, and 40 relationship types. The structured data was stored in the Neo4j graph structure database, and a knowledge graph of Chinese medical diagnosis and treatment of hepatitis B was constructed. The knowledge map is used as a structured data source to provide high-quality knowledge information for the medical question and answer system based on hepatitis B disease. Applying the deep learning method to the question identification and knowledge response of the question answering system makes the hepatitis B medical intelligent question answering system has important research and application significance. The question-and-answer system takes aim at hepatitis B, a public health problem in the world and leverages the advantages of traditional Chinese medicine for diagnosis and treatment. It provides a reference for doctors' disease diagnosis, treatment, and patient self-care. Its value is important for the treatment of hepatitis B disease.
本文使用真实的医学记录和中医诊治乙肝的网页，提取结构化的医学知识，共获取到 8563 个实体、96896 条关系、32 个实体类型和 40 种关系类型。结构化数据存储在 Neo4j 图结构数据库中，构建了中医诊治乙肝的知识图谱。知识图谱作为结构化数据源，为基于乙肝疾病的医疗问答系统提供高质量的知识信息。将深度学习方法应用于问答系统的问题识别和知识响应，使乙肝医学智能问答系统具有重要的研究和应用意义。问答系统以乙型肝炎为目标，乙型肝炎是全球公共卫生问题，利用中医在诊断和治疗方面的优势，为医生的疾病诊断、治疗和患者的自我护理提供了参考。它对乙型肝炎的治疗具有重要价值。
