基于语义网络构建风湿病证候生物学知识图谱

证候的量化、标准化研究一直是中医理论现代化的核心内容。近年来证候的物质基础成为证候标准化研究的热点。由于传统证候的评价体系众，多加之风湿病病程迁延，症状复杂多变，风湿病证候标准化问题一直未能解决。本课题组前期研究建立了中医药生物信息数据库，并初步发现了脾虚湿阻证类风湿关节炎、阴虚内热证系统性红斑狼疮等风湿病证候物质基础，验证了生物学特征作为证候研究的辨别条件的可行性。然而，目前风湿病证候的生物学研究进展并未得到系统梳理，与中医证候的关联性未被纳入到现有的证候相关数据库中。因此，本项目拟通过算法自学习的方式，在传统中医理论的指导下，以“语义网络”为骨架，标注分析现代证候研究进展及风湿科生物学研究，确立风湿病证候本体，建立风湿病证候生物学知识图谱。风湿病证候知识图谱的建立将系统展示医学信息的关联和共享，为风湿病的智能化诊疗提供理论依据和技术支持。

The quantification and standardization of syndromes have always been the core content of the modernization of TCM theory. In recent years, the material basis of syndromes has become a hotspot in the study of syndrome standardization. Due to the traditional evaluation system of syndromes and the prolonged course of rheumatism,and the standardization of rheumatism syndromes has not been solved. The research team established a biological information database of traditional Chinese medicine in the early stage, and initially found the material basis of rheumatoid syndromes such as rheumatoid arthritis of spleen deficiency and dampness syndrome, systemic lupus erythematosus of yin deficiency internal heat syndrome. However, the current biological research progress of rheumatism syndromes has not been systematically sorted out, and the relevance to TCM syndromes has not been incorporated into the existing syndrome-related databases. Therefore, This project intends to use algorithmic self-learning, under the guidance of traditional Chinese medicine theory, using the "semantic network" as the skeleton, to analyze the research progress of modern syndromes and the research of rheumatology biology, and to establish the knowledge of rheumatism syndrome biology. The establishment of the knowledge map of rheumatism syndromes will systematically display the association and sharing of medical information, providing theoretical basis and technical support for the intelligent diagnosis and treatment of rheumatism.