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Updated: Jan 20, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
[Rules of moxibustion for low back pain by ZHOU Meisheng based on data mining and knowledge graph technology]
Chi Wang1, Caifeng Zhu2, Jiayu Zhang1
1Second School of Clinical Medicine, Anhui University of CM, Hefei 230061, China.
Objective:
To analyze the rules of moxibustion for low back pain by ZHOU Meisheng by using data mining and knowledge graph technology.
Methods:
Taking the medical cases of moxibustion for low back pain from ZHOU Meisheng's legacy manuscripts and existing works as the research objects, information on disease types, symptoms, tongue manifestations, pulse conditions, syndrome patterns, moxibustion methods and acupoints were collected. Frequency statistics and community analysis were conducted by the ancient and modern medical record cloud platform V 2.3.7, cluster analysis of high-frequency acupoints was performed by SPSS26.0, association rule analysis of high-frequency acupoints was performed by SPSS Modeler 18.0, and the generated linked data were imported into Cytoscape 3.9.1 for complex network analysis. Knowledge graph of moxibustion for low back pain by ZHOU Meisheng was constructed based on the results of data mining. The data storage and display of knowledge graph were realized through the Neo4j 3.5.25 graph database, and the Cypher query language was used for knowledge graph retrieval and discovery.
Results:
A total of 219 medical cases were collected, involving 14 disease types, 85 related clinical symptoms, 5 related TCM syndrome types, and 6 moxibustion methods. The acupoints were mostly attributed to the governor vessel, the bladder meridian of foot-taiyang, non-meridian and non-acupoint areas. The core prescription of acupoints derived from complex network analysis included tender points, Shenshu (BL23), Jinsuo (GV8), Yinjiao (CV7), Yaoyangguan (GV3), Yanglingquan (GB34), which were largely coincides with high-frequency acupoints. Cluster analysis obtained 4 cluster combinations. Community analysis yielded 6 communities, each corresponding to different acupoints.The constructed knowledge graph contained 187 nodes and 696 relationships, by retrieving clinical elements related to low back pain, the disease-moxibustion association graph, disease-acupoint association graph, accompanying symptom-acupoint association graph and syndrome type-matching point association graph were obtained.
Conclusion:
When treating low back pain with moxibustion, ZHOU Meisheng adopts the principle of promoting circulation, distinguishing diseases to determine the treatment, selecting acupoints according to the diseases, and matching points according to the symptoms.And taking tender points, Shenshu (BL23), Jinsuo (GV8), Yinjiao (CV7), Yaoyangguan (GV3), Yanglingquan (GB34) as core acupoints, combined with tenderness point selection, acupoint selection based on meridian and zangfu syndrome differentiation, "sunshine area" acupoint selection, yin-yang acupoint matching. Additionally, he skillfully employs special points, such as Zhongzhu (KI15) and ear tips, pays attention to the reform of moxibustion tools, and innovates the moxibustion techniques, using distinctive moxibustion tools and methods to treat low back pain.
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