摘要
目的探讨颜正华教授治疗痞满的用药规律与经验。方法收集颜正华教授治疗痞满的病案,采用关联规则apriori算法、复杂系统熵聚类等无监督数据挖掘方法,确定处方中各种药物的使用频次及药物之间的关联规则,分析颜正华教授治疗痞满的用药经验。结果对筛选出的143首处方进行分析,确定处方中药物的使用频次、药物之间的关联规则,挖掘出51个核心组合和12首新处方。结论颜正华教授治疗痞满多用疏肝理气、活血消胀之品。
Objective To analyze the medication rule and experience of professor Yah Zhenghua for gastric stuffiness by using Traditional Chinese Medicine （TCM） inheritance support system. Methods Yah Zhenghua＇s prescriptions for gastric stuffiness were collected and input into TCM inheritance support system. The composing principles were analyzed by using data mining methods such as revised mutual information, complex system entropy cluster and unsupervised hierarchical cluster. Results Based on the analysis of 143 prescriptions, the frequency of each herb and association rules among the herbs were computed, 51 core combinations and 12 new prescriptions were mined out from the database. Conclusion Professor Yan Zhenghua is good at soothing the liver, regulating qi, simulating the circulation of blood to relieve gastric stuffiness.
出处
《中国中医药信息杂志》
CAS
CSCD
2013年第3期31-33,共3页
Chinese Journal of Information on Traditional Chinese Medicine
基金
国家科技支撑计划(2007BAI10B01)
北京市自然科学基金(7112075)
北京市中医药科技发展基金(JJ-2010-70)
北京中医药大学科研创新团队项目(2011-CXTD-14)
北京中医药大学自主选题项目(JYB22-JS020)
关键词
颜正华
痞满
关联规则
聚类算法
Yan Zhenghua
gastric stuffiness
association rules
clustering algorithm
