关联规则研究及在中风诊治中的应用分析

Research on Association Rules Mining and Application of Apoplexy Treatment

为了更好地促进国粹中医药的研究发展,文中研究了关联规则及实现该技术的代表算法Apriori和FP-growth。收集了临床出现的各种中风症状,整理了历代医家在诊治中风过程中使用的方剂、药物,采用基于Apriori算法的关联规则技术对其挖掘,萃取出有利于医学研究的知识。通过挖掘得到的药物高频项集及药物之间的依赖关系,发现了一些治疗效果较好的药和药对;通过症状与药物之间的依赖关系,发现了治疗高频症状的核心药物;这将对中风的诊断和治疗提供有力的支持。

To help and direct the traditional Chinese medical science research,do a research on association rules,especially on the representative algorithms of Apriori and FP-growth.A large amount of data about apoplexy symptoms and related cure prescription and medicines are collected.Useful information is discovered using Apriori algorithm from the data.Based on the frequent itemsets and dependency relationships of medicines,a batch of effective medicine pairs are discovered;The core medicines to cure high-frequency apoplexy symptoms are found through the dependency relationships of symptoms and medicines;These discoveries give strong support to make a diagnosis and give treatment in apoplexy.