世界中医药
文章摘要
引用本文:黄盛1,祁烁2,李会龙2,陈晓珩2,李哲2,付金香1,李伟强2,丁治国2.基于中医传承辅助系统治疗甲状腺结节用药规律分析[J].世界中医药,2020,(07):.  
基于中医传承辅助系统治疗甲状腺结节用药规律分析
Analysis on the Prescription Regulation For Thyroid Nodules By Using Traditional Chinese Medicine Inheritance Support System
投稿时间:2019-08-11  
DOI:10.3969/j.issn.1673-7202.2020.07.013
中文关键词:  甲状腺结节;用药规律;数据挖掘  中医传承
English Keywords:Thyroid nodules  Composition principles  Data mining  TCM inheritance
基金项目:北京中医药大学新奥基金项目(2017-XAJLJJ-017);北京市薪火传承“3+3”工程项目(2016-SZ-C-61)
作者单位
黄盛1,祁烁2,李会龙2,陈晓珩2,李哲2,付金香1,李伟强2,丁治国2 1 北京中医药大学第一临床医学院北京100700 2 北京中医药大学东直门医院北京100700 
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中文摘要:
      目的:借助中医传承辅助平台系统软件,分析中医药治疗甲状腺结节的组方用药规律。方法:通过检索中国知网、维普数据库、万方数据库近10年来中医药治疗甲状腺结节的文献为数据源,筛选并建立方剂数据库,采用频数统计、关联原则、复杂系统熵聚类等数据挖掘方法,对核心药物及其归经、性味、组方规律、核心组合等进行分析研究。结果:共筛选出符合标准的方剂103首,涉及中药145种,分析出18个使用频次20及20以上的药物、32个常用药对,挖掘出14个核心药物组合、7个新处方。结论:借助中医传承辅助系统分析中医药治疗甲状腺结节的用药规律,有助于为临床治疗提供新思路,并为选方用药提供参考依据。
English Summary:
      To analyze prescription regularity of TCM prescription and medication for the treatment of thyroid nodules,based on the traditional Chinese medicine (TCM) inheritance support platform system.Methods:This study chose academic literatures related to TCM treatment of thyroid nodules in CNKI database,VIP database,Wanfang database over the past 10 years as the data source,screened and established database to analyze the core drugs and their channel tropism,property and flavor,compatibility law,and core composition,by means of frequency statistics,association rules,and complicated system entropy clustering and other data mining methods.Results:A total of 103 formulas selected and 145 kinds of Chinese medicines were involved.And the analysis showed that there were 18 drugs with usage frequency of 20 and more than 20,32 common drug pairs.And 14 core drug combination,and 7 new prescriptions were explored.Conclusion This research,which is based on TCM inheritance support software,to analyze prescription regularity of TCM for the treatment of thyroid nodules,is helpful to provide new ideas for clinical treatment and provide a reference for prescription drugs.
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