Knowledge Graph Construction of Chronic Kidney Disease Diagnosis and Treatment with Traditional Chinese Medicine

Background. The purpose of this study is to construct a knowledge graph of chronic kidney disease (CKD) diagnosis and treatment with traditional Chinese medicine (TCM), reorganize its knowledge, and display it. It allows the inheritance, development, and utilization of CKD diagnosis and treatment experiences with TCM in a standard and scientific manner. Methods. First, we constructed a knowledge framework for TCM diagnosis and treatment on the basis of the Chinese Pharmacopoeia, government projected textbook, and the current TCM diagnosis and treatment standards. Then, we collected and sorted the electronic medical records of TCM inpatients, extracting and normalizing the diagnoses, symptoms, syndromes, prescriptions, and other diagnosis and treatment information, creating the knowledge base of TCM diagnosis and treatment for CKD. Finally, we stored TCM diagnosis and treatment CKD knowledge in Neo4j graph database, which refers to the knowledge framework and knowledge base. The frequent patterns and complex network knowledge mining methods are integrated to construct the TCM diagnosis and treatment CKD knowledge graph. Results. The knowledge graph of CKD diagnosis and treatment with TCM was constructed, including 807 nodes and 10476 relationships, which are 273 diagnoses, 130 symptoms, 34 syndromes, 370 Chinese herbal medicine (CHM) nodes, and 5483 diagnosis-symptom, 1349 diagnosis-syndrome, 3644 syndrome-CHM relationships. Conclusion. The knowledge graph provides rich knowledge of TCM diagnosis and treatment of CKD, which is helpful to inherit the clinical experience of TCM diagnosis and treatment of CKD and assist clinical diagnosis and treatment of CKD.