关联规则挖掘在临床诊断中的应用研究

将关联规则挖掘应用于临床疾病诊断工作,力求找出数据中各层次因素间的关联关系,挖掘疾病数据库中的关联规则。通过实例试图发现吸烟、环境污染、职业性致肺癌因素、肺部慢性疾病等因素与肺癌的发生与诊断间的关联关系,从而发现肺癌疾病与它产生的可能因素间的规则,利用规则模式指导肺癌的诊断与预防。并期望以此为例研究关联规则挖掘在疾病诊断各方面的应用。

Application of association rules mining in the clinical diagnosis

Association rule mining is a crucial method of the technology of data mining to solve the problems of complicated data in large data base.This paper applies association rule to the diagnosis of clinical diseases,trying to find the relationship between facts of different levels in data base,in order to get known the association rules in disease data base.Through analyzing examples,this paper attempts to study the association between the facts like smoking,environmental pollution,occupational diseases,chronic lung diseases and lung cancer,from the result of which to explore the rules between lung cancer and the facts leading to its happening.This mode of rule will be helpful in the diagnose and prevention of lung cancer.The writer hopes that this case can be seen as an application of association rule mining in disease diagnoses.