Objective To comprehensively sort out and visually analyze the research status, hotspots and trends of knowledge graph technology in the field of traditional Chinese medicine (TCM) from the perspectives of bibliometrics and global patents, provide references for in-depth research and development in this field. Methods The relevant Chinese and English literature published between January 1, 2012, and December 31, 2025, was systematically retrieved from the CNKI, Wanfang, VIP, and Web of Science databases. Using tools such as CiteSpace, VOSviewer, and Excel, we performed bibliometric and visual analyses of publication trends, institutional and author collaboration networks, journal sources, and keyword co-occurrence and evolution. Additionally, we analyzed global patent applications from the Incopat database, focusing on application trends, geographical distribution, applicants, and technical themes. Results A total of 745 valid publications were included (618 in Chinese, 127 in English) and 432 patent families. Research on knowledge graph technology in TCM is in a phase of rapid development. Current hotspots focus on refining knowledge extraction techniques, developing KG-assisted diagnosis and treatment systems, intelligent question-answering, and synergistic applications with large language models. The field is moving toward deeper interdisciplinary integration and clinical application . China occupies a dominant position in both research output and patent applications (96% share), with established collaboration networks. However, cross-regional and interdisciplinary cooperation requires further strengthening. Conclusion Research on knowledge graph technology in the field of traditional Chinese medicine is deeply evolving from fundamental construction to intelligent applications. Despite China’s quantitative advantage in patents, challenges persist, including a relative lack of high-value patents, technical homogenization, and insufficient international competitiveness.

bibliometrics  /  knowledge graph  /  visual analysis  /  traditional Chinese medicine  /  patent analysis  /  CiteSpace