The Research on Knowledge Graph Construction of Jiezhai Gong' s Obstetric and Gynecological Medical Cases Based on Neo4j

Objective: To construct a visual knowledge graph of Jiezhai Gong's Obstetric and Gynecological Medical Cases using knowledge graph technology. By inputting Cypher queries, we enable interactive visualization of relevant content, intuitively presenting the logical relationships among “diseases, prescriptions, and medications” while uncovering hidden knowledge. Methods: Using Jiezhai Gong's Obstetric and Gynecological Medical Cases as the data source, we applied knowledge graph construction techniques—including entity linking, relation extraction, and knowledge fusion—to build a “disease-prescription-medication” knowledge graph in the Neo4j graph database. Results: A total of 33 disease terms were standardized, 205 entities extracted, and 587 relationships established, successfully constructing the knowledge graph for Jiezhai Gong's Obstetric and Gynecological Medical Cases. Conclusion: The knowledge graph of Jiezhai Gong's Obstetric and Gynecological Medical Cases on Obstetrics visually demonstrates the relationships among diseases, prescriptions, and Chinese herbal medicines, providing diagnostic decision support and treatment recommendations for clinical practice in traditional Chinese medicine (TCM) obstetrics, while also facilitating the digital preservation of ancient TCM texts.