基于数据挖掘的中医治疗风湿病组方规律分析

Analysis on medication rules of traditional Chinese medicine prescriptions for rheumatism based on data mining

目的探讨中医治疗风湿病的组方用药规律。方法收集中医治疗风湿病的处方,基于中医传承辅助平台软件构建数据库,采用关联规则和复杂系统熵聚类算法,确定处方中各药物及药物组合的使用频次,挖掘药物之间的关联规则等。结果高频次药物包括当归、甘草、白芍、黄芪、羌活、丹参等;高频次药物组合包括"当归,白芍""甘草,当归""川芎,当归"等。置信度为0.7以上的关联规则包括"香附->当归""鸡血藤->当归""川芎->当归"。结论风湿病的治疗处方多采用补气血、祛风湿、活血化瘀类药物,体现中医标本兼顾、辨证论治的治疗原则。

Objective To explore the medication rules of Chinese medicine in the treatment of rheumatic diseases. Methods The traditional Chinese medicine prescriptions for the treatment of rheumatism were collected and the related database was built based on Traditional Chinese Medicine Inheritance Support System （TCMISS）, then the data were analyzed by Apriori algorithm and complex system entropy clustering algorithm in TCMISS to acquire the frequency of single medicine, the frequency of drug combinations, the association rules, etc. Results The highest frequency drugs included Angelicae Sinensis Radix, Glycyrrhizae Radix et Rhizoma, Paeoniae Radix Alba, Astragali Radix, Notopterygii Rhizoma et Radix, Salviae Miltiorrhizae Radix et Rhizoma, etc. The most frequent drug combinations included “Angelicae Sinensis Radix, Paeoniae Radix Alba” “Glycyrrhizae Radix et Rhizoma, Angelicae Sinensis Radix” “Chuanxiong Rhizoma, Angelicae Sinensis Radix”, etc. The association rules with confidence coefficient more than 0.7 were “CyperiRhizoma-〉Angelicae Sinensis Radix” “Spatholobi Caulis-〉Angelicae Sinensis Radix” “Chuanxiong Rhizoma-〉AngelicaeSinensis Radix”, etc. Conclusion The traditional Chinese medicine prescriptions for rheumatism mostly contained the drugs with the effects of benefiting Qi, nourishing blood, dispelling pathogenic wind, removing dampness, promoting blood circulation and removing blood stasis, which demonstrated the therapeutic principle of looking into both roots cause and symptoms, and treatment based on syndrome differentiation.