TCMRD - KG: innovative design and development of rheumatology knowledge graph in ancient Chinese literature assisted by large language models

作者：Haotian Li, Congmin Xia, Youjuan Hou, Shengshou Hu, Yanjun Liu, Quan Jiang · 发表于：Frontiers in Pharmacology · 年份：2025 · DOI：10.3389/fphar.2025.1535596 · 被引用次数：15 · 研究领域：Traditional Chinese Medicine Studies、Biomedical Text Mining and Ontologies、Machine Learning in Healthcare

Introduction: Rheumatic immune diseases are a type of immune-inflammatory disease that affects muscles, bones, joints, and surrounding soft tissues. They have a long course and a high disability rate, seriously affecting the quality of life of patients. Traditional Chinese medicine plays an important role in the diagnosis and treatment of rheumatic immune diseases. The unique theoretical system and rich treatment methods of traditional Chinese medicine are preserved in ancient Chinese medical books. Methods: This study takes the content related to rheumatism in ancient traditional Chinese medicine books as the research object, integrates ontology theory and technology into the knowledge graph, and realizes the reconstruction of traditional Chinese medicine information knowledge. It provides a basic data structure for data mining and knowledge discovery. Results: This study is the first rheumatism-specific knowledge graph constructed based on ancient traditional Chinese medicine books. It has explored the construction method of a knowledge graph from ancient books by combining automatic labeling of mainstream large language models with manual review. Considering the knowledge characteristics of ancient traditional Chinese medicine books, where existing word segmentation technology struggles to accurately reproduce the original meaning, a new type of entity extraction method is proposed. Discussion: This provides an important foundation for improving the clinical diagnosis and ...