摘要
目的基于数据挖掘方法对《伤寒论》方证进行知识挖掘。方法采用中医处方智能分析系统(CPIAS)对《伤寒论》112首方剂的知识点进行量化表达。结果初步实验效果较好,机器的认识与传统《伤寒论》的认识基本相符,吻合率高达98%。结论本研究实现了《伤寒论》方证的君、臣、佐、使排序,气、味、归经规律及辨证处方规律等方面的知识挖掘。
Objective To realize knowledge mining of prescriptions and syndromes knowledge in Treatise on Febrile Diseases by data mining method.Methods By means of Chinese Medicine Prescription Intelligent Analysis System,knowledge points of 112 prescriptions in Treatise on Febrile Diseases were quantitatively expressed.Results Compared with the traditional understanding of Treatise on Febrile Diseases,the experimental results showed that the prescription concerns was determined with an analysis accuracy rate of 98%.Conclusion We achieve the ranking of monarch,minister,assistant and guide,find the law of composition with four natures,five tastes and the features of channel tropism,and complete the knowledge mining of prescription rules in Treatise on Febrile Diseases.
出处
《中国中医药信息杂志》
CAS
CSCD
2012年第4期31-34,共4页
Chinese Journal of Information on Traditional Chinese Medicine
基金
国家自然科学基金(81072745)
关键词
数据挖掘
中医处方智能分析系统
伤寒论
方证
data mining
Chinese Medicine Prescription Intelligent Analysis System
Treatise on Febrile Diseases
prescriptions and syndromes
