Abstract

To explore the methods of the explicitation of implicit knowledge and the construction of knowledge graph on moxibustion in medical case records of ZHOU Mei-sheng's Jiusheng. The medical case records data of Jiusheng was collected, the frequency statistic was analyzed based on Python3.8.6, complex network analysis was performed using Gephi9.2 software, community analysis was performed by the ancient and modern medical case cloud platform V2.3.5, and analysis and verification of correlation graph and weight graph were proceed by Neo4j3.5.25 image database. The disease systems with frequency≥10 % were surgery, ophthalmology and otorhinolaryngology, locomotor, digestive and respiratory systems. The diseases under the disease system were mainly carbuncle, arthritis, lumbar disc herniation and headache. The commonly used moxibustion methods were fumigating moxibustion, blowing moxibustion, direct moxibustion and warming acupuncture. The core prescription of points obtained by complex network analysis included Yatong point, Zhiyang(GV 9), Sanyinjiao(SP 6), Dazhui(GV 14), Zusanli(ST 36), Lingtai(GV 10), Xinshu(BL 15), Zhijian point and Hegu(LI 4), which were basically consistent with high-frequency points. A total of 6 communities were obtained by community analysis, corresponding to different diseases. Through the analysis of correlation graph, 13 pairs of strong association rule points were obtained. The correlation between Zhiyang(GV 9)-Dazhui(GV 14) and Yatong point-Lingtai(GV 10) was the strongest. The acupoints with high correlation with Yatong point were Zhiyang(GV 9), Lingtai(GV 10), Dazhui(GV 14), Zusanli(ST 36) and Sanyinjiao(SP 6). In the weight graph of the high-frequency disease system, the relationship of the first weight of the surgery system disease was fumigating moxibustion-carbuncle-Yatong point, and the relationship of the first weight of the ophthalmology and otorhinolaryngology system disease was blowing moxibustion-laryngitis-Hegu (LI 4). The results of correlation graph and weight graph are consistent with the results of data mining, which can be used as an effective way to study the knowledge base of moxibustion diagnosis and treatment in the future.探究周楣声《灸绳》医案灸法隐性知识显性化及其知识图谱构建的方法。收集《灸绳》医案数据,基于Python3.8.6进行频数统计分析,利用Gephi9.2软件进行复杂网络分析,登录古今医案云平台V2.3.5进行社团分析,并运用Neo4j3.5.25图数据库进行关联图谱和权值图谱的分析及验证。出现频率≥10%的疾病系统分别为外科、五官、运动、消化和呼吸系统。疾病系统下属疾病以痈、关节炎、腰椎间盘突出症、头痛为主。治疗常用灸法为熏灸、吹灸、直接灸和温针灸。复杂网络分析所得腧穴核心组方为压痛穴、至阳、三阴交、大椎、足三里、灵台、心俞、指尖、合谷,基本与高频腧穴相一致。社团分析共得到6个社团,分别与不同疾病相对应。关联图谱分析得到强关联规则穴对13条,至阳-大椎、压痛穴-灵台的关联性最强,与压痛穴关联性较高的腧穴为至阳、灵台、大椎、足三里、三阴交。高频疾病系统权值图谱中,外科系统疾病权值排名第一的关系为熏灸-痈-压痛穴,五官系统疾病权值排名第一的关系为吹灸-喉炎-合谷。关联图谱及权值图谱所得结论与数据挖掘结果相一致,可作为未来研究灸法诊疗知识库的有效途径。.

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