Factors Associated With Coronary Heart Disease-Related Research And Annalysis And Implemetation Of The Rules

This article mainly researches on the combination of Association Rule Mining techonology and Psychosomatic Medicine field, offering a solution of how to analysize a large number of CHD patients'records by adopting an association rules data mining techonology and thus aiming at achieving new and useful knowledge by revealing the pathogenic rules of some frequent factor combinations which causes CHD.The subject focuses on the design and realisation of calculation methods about Association Rule Mining, and analysizes the problems and shortcomings of classic frequent itemset generating of Apriori. It also focuses on the improving and achieving of classic calculation methods, and conducts experiments on the environment of Access CHD database to find out the frequent fields combinations of field values of disease record and CHD degree field values. By pre-given support and confidence to measure those frequent fields combinations and thus deduce reasonable CHD incidence association rules.The overall arrangements of this article are as follows: Part I is foreword, introducing the research background, purpose, and significance of the the subject. Part II focuses on the data mining and relavant concepts and calculation methods of assiciation rules, to recall the relevant field of work; Part III is about the design and achieveing of frequent itemset generation, including the analysis on classic calculation of Apriori and the improving, design, achieving and experimental results analysis; Part IV is the summary and outlook. It's believed to be of great significance to do researches on the CHD patients'risk factors by adopting an association rules data mining techonology and that will provide a basis for the disease prevention of community health care.