公开(公告)号：US20240412838A1

公开(公告)日：2024-12-12

申请号：US18667299

申请日：2024-05-17

Applicant: HENAN UNIVERSITY OF SCIENCE AND TECHNOLOGY

Inventor： Mingchuan Zhang ,  Lin Wang ,  Qingtao Wu ,  Wenxuan Xu ,  Junlong Zhu ,  Xuhui Zhao ,  Muhua Liu ,  Ruijuan Zheng ,  Zhihang Ji ,  Moli Zhang

IPC: G16H20/10 ,  G06N3/0464 ,  G06N3/08

Abstract: A knowledge graph-based method for recommending traditional Chinese medicine (TCM) prescriptions is provided. The method integrates a knowledge graph embedding model, a multi-head attention mechanism, graph convolutions, and other techniques to combine graph features with a recommendation system, for comprehensively considering patient conditions to recommend TCM prescription. Taking TCM case description texts as the research object and integrating with TCM knowledge graph information, the method draws from the clinical experience of renowned TCM experts and fully considers various individual factors such as medicinal properties, efficacy, medical conditions, and patient constitutions. Based on the holistic principles of TCM and the ideology of syndrome differentiation and treatment, the method selects different herbal combinations based on varying symptoms and medical conditions of patients. The proposed TCM prescription recommendation method, incorporating the knowledge graph, considers the complex relationships between individual signs as well as symptoms and medications.