The Application of Improved Apriori Algorithm in Axthma Cases Data Mining
ZHU Xijun
CHEN Yanan
DONG Guohua
Abstract：TCM asthma case contains a lot of empirical data obtained by physicians in clinical diagnosis , using data correlation analysis methods to mine the rule of medicine prescription compatibility and the inci‐dence relation between symptoms and medication .The article analyzes and studies the performance and dis‐advantages of Apriori algorithm by examples ,and proposes an improved Apriori algorithm called Apriori‐BSO algorithm based on the fast response of computer's logic operations in bit strings .Combined with the classic Apriori algorithm ,it then compares the running aging of the two algorithms to mine the frequent item sets and strong association rules .The experiments showed that the improved Apriori algorithm is val‐uable in the data analysis of asthma cases w hen it is applied to the correlation analysis of asthma medication data and the symptoms‐medication data in mining the rule of medicine prescription compatibility and the in‐cidence relation between symptoms and medication .
Keywords：correlation analysisApriori algorithmsasthmabit strings operation
Publication Date：2015-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 8-14 )