Correlation analysis of TCM diagnosis and treatment based on Apriori algorithm with grouping association
10.7687/j.issn1003-8868.2017.08.034
- VernacularTitle:基于分组联接的Apriori算法的中医药诊疗关联性分析
- Author:
bin Hong LI
1
;
ning Wu TONG
Author Information
1. 陕西中药大学附属医院
- Keywords:
association rule;
natural association;
grouping association;
frequent itemset;
Apriori algorithm
- From:
Chinese Medical Equipment Journal
2017;38(8):34-37
- CountryChina
- Language:Chinese
-
Abstract:
Objective To analyze the correlation between the TCM diagnosis and treatment data to provide support for scientific research and clinical treatment.Methods The characteristics of TCM diagnosis and treatment data were analyzed.An improved Apriori algorithm with grouping association was put forward,and association analysis on the data from the encephalopathy database of some hospital was carried out to verify the feasibility of the algorithm.Results Grouped operation was executed for association properties to reduce the association between noncorrelated data,so that the efficiency of the algorithm was enhanced greatly.Conclusion Improved Apriori algorithm with grouping association consumes shorter time than the classical one,and thus is worthy promoting in TCM diagnosis and treatment data application.
