[1]覃堃 施展△.古籍中治疗筋病外用药规律的数据挖掘研究[J].中国中医骨伤科杂志,2021,29(02):27-30.
　QIN Kun SHI Zhan.Chinese Medical Classics Data Mining Research on the Rule ofExternal Applicative Drugs in the Treatment of Sinew Disease[J].Chinese Journal of Traditional Medical Traumatology & Orthopedics,2021,29(02):27-30.
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古籍中治疗筋病外用药规律的数据挖掘研究()
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《中国中医骨伤科杂志》[ISSN:1005-0205/CN:42-1340/R]

卷:
第29卷
期数:
2021年02期
页码:
27-30
栏目:
文献研究
出版日期:
2021-02-15

文章信息/Info

Title:
Chinese Medical Classics Data Mining Research on the Rule ofExternal Applicative Drugs in the Treatment of Sinew Disease
文章编号:
1005-0205(2021)02-0027-04
作者:
覃堃1; 2 施展1△
1中国中医科学院中医临床基础医学研究所(北京,100700)2北京中医药大学
Author(s):
QIN Kun1; 2 SHI Zhan1△
1Institute of Basic Research in Clinical Medicine,China Academy of Chinese Medical Sciences,Beijing 100700,China; 2Beijing University of Chinese Medicine,Beijing 100029,China.
关键词:
筋病;  外用药;  外治;  数据挖掘;  组方配伍;  用药规律
Keywords:
sinew disease;  internal drugs;  data mining;  association rules;  formula compatibility;  medication rules
分类号:
R274.39
文献标志码:
A
摘要:
目的:探讨《中华医典》中治疗筋病外用方剂的用药与组方规律,以期对筋病的中药外用治疗及新药研发提供参考。方法:收集整理《中华医典》单机版(V5.0)中治疗筋病共63首外用方剂,涉及136味中药,录入中医传承辅助系统(V2.5),采用改进的互信息法、关联规则、核心算法、熵层次聚类,统计单药、对药、角药出现频次,并分析关联规则、提取核心组合、发现新方,进行数据挖掘研究。结果:最常见单药是白芷(25次,占39.68%)、当归(25次,占39.68%),最常见对药是白芷-当归(15次,占23.81%)、没药-乳香(15次,占23.81%),最常见角药是白芷-川芎-当归(12次,占19.05%); 关联度最高的药物组合是没药→乳香(置信度为0.937 5); 得到14组3味或4味药的核心组合,核心药物为白芷、当归、乳香、川芎、没药等; 得到外用治疗筋病7个新候选处方。结论:提示中药外用治疗筋病以及新药研发时,单药、对药、角药优先考虑白芷、当归、川芎,配伍优先考虑没药配伍乳香,核心方剂优先考虑血竭、铅丹、乳香等,新候选处方配伍考虑血竭、铅丹、乳香、生姜等。
Abstract:
To investigate prescription regularity of external herbal medicines in the treatment of sinew disease in traditional Chinese medicine(TCM)inheritance auxiliary platform,so as to provide basis for clinical treatment on sinew disease,research and develop new medicines for treating sinew disease.Methods:A total of 63 traditional Chinese medicine prescriptions with 136 herbals from Encyclopedia of Traditional Chinese Medicine were collected and input into TCM inheritance auxiliary platform version 2.5.The method of improved mutual information entropy clustering,association rules,complex systems entropy clustering and unsupervised entropy hierarchical clustering were used to count the frequency of the single,pairs and triangle drugs.Association rules of drugs,evolution and extraction of combination of the core drugs were analyzed to perform newfound prescription.Results:The most commonly used herbal medicine was Angelica dahurica(25,39.68%)and Angelica(25,39.68%).The most common pair of drugs were Angelica dahurica-Angelica(15,23.81%)and Myrrh-Frankincense(15,23.81%).The most common triangle drugs were Angelica dahurica-Rhizoma Chuanxiong-Angelica(12,19.05%).The drugs combination with high correlation was Myrrh→Frankincense with confidence of 0.937 5.14 sets of triangle or quadruple drugs were extracted.The core drugs were Angelica dahurica,Angelica,Frankincense,Rhizoma Chuanxiong Myrrh,and 7 new prescriptions were provided.Conclusion:This study shows that Angelica dahurica,Angelica and Rhizoma Chuanxiong should be considered first for the single,pairs and triangle drugs; Myrrh with Frankincense should be considered first for compatibility of medicines; Dragon’s blood,Red lead and Frankincense should be considered first for core formula drugs.Dragon’s blood,Red lead,Frankincense and Ginger should be considered first for the candidate prescription during the research and development of new external drugs on treating sinew disease.

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备注/Memo

备注/Memo:
基金项目:北京市卫生与健康科技成果和适宜技术推广项目(2018-TG-85)中国中医科学院第十三批基本科研业务费自主选题项目(Z0646)
△通信作者 E-mail:shizhan209@163.com
更新日期/Last Update: 2021-02-15