关联规则数据挖掘技术在医疗服务中的应用

发布时间：2018-02-28 03:48

本文关键词： 关联规则挖掘婚检儿童肺炎　出处：《云南大学》2012年硕士论文　论文类型：学位论文

【摘要】：随着计算机科学与技术的广泛应用,各学科领域产生的数据量剧增。为了在这些数据中发现有价值的知识,人们利用数据挖掘的方法来解决这一问题,而关联规则挖掘的应用是数据挖掘领域中一个重要的研究课题。随着关联规则挖掘技术的日渐成熟,如何将这一方法运用于从大量的医学数据中找出其内在关联规则的研究,为临床疾病监测、药物治疗效果的评价及疾病预防提供有效依据,更是一个新的研究内容。本文利用关联规则挖掘的经典Apriori算法对医学数据进行数据挖掘分析。首先使用Apriori算法寻找数据库中数据的频繁项集,然后根据频繁项集生成强关联规则,以发现海量数据中项集之间有用的关联关系或模式。最终的目的是对关联规则挖掘在临床疾病监测、药物治疗效果的评价以及疾病的预防等方面的应用进行分析研究。列举关联规则挖掘对婚检数据和儿童肺炎药物治疗效果的数据进行分析,得到的结果可为婚检人员提供全面健康体检项目,也可为儿童肺炎治疗的规范性用药提供决策依据。本论文在详尽分析数据挖掘和关联规则挖掘特点的基础上,阐述和分析了关联规则挖掘的Apriori算法；分析了医学数据的特点,研究了关联规则在相关疾病数据中的应用,并且使用Apriori算法对婚检数据中艾滋病、梅毒、乙肝、丙肝之间的关系和儿童肺炎用药数据中药物治疗效果进行了数据挖掘及分析研究,研究结果可为婚检人员制定全面科学体检方案。对儿童肺炎病例的关联规则挖掘研究结果可以为其规范性用药提供决策依据,在临床实践中可以建立儿童肺炎治疗用药字典,从治疗效果和维护患者利益的角度出发,合理选择用药,制定儿童肺炎病治疗最佳用药方案,改善治疗效果,提高治疗效率,也可作为药品审计依据。研究结果表明,在医疗卫生领域的疾病预防和药物治疗等方面的数据中进行数据挖掘处理和分析是一个值得重视的研究方向。
[Abstract]:With the wide application of computer science and technology, the amount of data generated in various disciplines has increased dramatically. In order to find valuable knowledge in these data, people use the method of data mining to solve this problem. The application of association rules mining is an important research topic in the field of data mining. With the development of association rules mining technology, how to apply this method to find out the internal association rules from a large amount of medical data, To provide effective basis for clinical disease monitoring, evaluation of therapeutic effect and disease prevention. In this paper, the classical Apriori algorithm of association rule mining is used to analyze the medical data. Firstly, the Apriori algorithm is used to find the frequent itemsets of the data in the database. Then strong association rules are generated according to frequent itemsets to discover useful association relationships or patterns among itemsets in massive data. The ultimate goal is to mine association rules in clinical disease monitoring. The evaluation of drug treatment effect and the application of disease prevention are analyzed. The association rule mining is cited to analyze the data of antemarital examination and the effect of drug therapy on pneumonia in children. The results can provide comprehensive health examination items for premarital medical examiners, as well as the decision basis for the standardized drug use in the treatment of pneumonia in children. This paper analyzes the characteristics of data mining and association rule mining in detail. This paper expounds and analyzes the Apriori algorithm of association rule mining, analyzes the characteristics of medical data, studies the application of association rules in related disease data, and uses Apriori algorithm to analyze HIV / AIDS, syphilis and hepatitis B in premarital examination data. The relationship between hepatitis C and the effect of drug therapy in children with pneumonia were analyzed and analyzed. The results of the study can make a comprehensive scientific check-up plan for the premarital examiners. The results of association rules mining for children pneumonia cases can provide the decision basis for their normative drug use, and can be used in clinical practice to establish a drug dictionary for the treatment of children's pneumonia. From the point of view of therapeutic effect and maintenance of patients' interests, rational choice of drug use, formulation of the best drug use plan for the treatment of pneumonia in children, improvement of therapeutic effect and improvement of therapeutic efficiency can also be used as the basis for drug audit. Data mining and analysis in disease prevention and drug treatment in medical and health field is an important research direction.
【学位授予单位】：云南大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：R319;TP311.13

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