本文關鍵詞： 關聯(lián)規(guī)則挖掘 婚檢 兒童肺炎　出處：《云南大學》2012年碩士論文　論文類型：學位論文

【摘要】：隨著計算機科學與技術的廣泛應用,各學科領域產(chǎn)生的數(shù)據(jù)量劇增。為了在這些數(shù)據(jù)中發(fā)現(xiàn)有價值的知識,人們利用數(shù)據(jù)挖掘的方法來解決這一問題,而關聯(lián)規(guī)則挖掘的應用是數(shù)據(jù)挖掘領域中一個重要的研究課題。隨著關聯(lián)規(guī)則挖掘技術的日漸成熟,如何將這一方法運用于從大量的醫(yī)學數(shù)據(jù)中找出其內(nèi)在關聯(lián)規(guī)則的研究,為臨床疾病監(jiān)測、藥物治療效果的評價及疾病預防提供有效依據(jù),更是一個新的研究內(nèi)容。本文利用關聯(lián)規(guī)則挖掘的經(jīng)典Apriori算法對醫(yī)學數(shù)據(jù)進行數(shù)據(jù)挖掘分析。首先使用Apriori算法尋找數(shù)據(jù)庫中數(shù)據(jù)的頻繁項集,然后根據(jù)頻繁項集生成強關聯(lián)規(guī)則,以發(fā)現(xiàn)海量數(shù)據(jù)中項集之間有用的關聯(lián)關系或模式。最終的目的是對關聯(lián)規(guī)則挖掘在臨床疾病監(jiān)測、藥物治療效果的評價以及疾病的預防等方面的應用進行分析研究。列舉關聯(lián)規(guī)則挖掘?qū)闄z數(shù)據(jù)和兒童肺炎藥物治療效果的數(shù)據(jù)進行分析,得到的結果可為婚檢人員提供全面健康體檢項目,也可為兒童肺炎治療的規(guī)范性用藥提供決策依據(jù)。本論文在詳盡分析數(shù)據(jù)挖掘和關聯(lián)規(guī)則挖掘特點的基礎上,闡述和分析了關聯(lián)規(guī)則挖掘的Apriori算法；分析了醫(yī)學數(shù)據(jù)的特點,研究了關聯(lián)規(guī)則在相關疾病數(shù)據(jù)中的應用,并且使用Apriori算法對婚檢數(shù)據(jù)中艾滋病、梅毒、乙肝、丙肝之間的關系和兒童肺炎用藥數(shù)據(jù)中藥物治療效果進行了數(shù)據(jù)挖掘及分析研究,研究結果可為婚檢人員制定全面科學體檢方案。對兒童肺炎病例的關聯(lián)規(guī)則挖掘研究結果可以為其規(guī)范性用藥提供決策依據(jù),在臨床實踐中可以建立兒童肺炎治療用藥字典,從治療效果和維護患者利益的角度出發(fā),合理選擇用藥,制定兒童肺炎病治療最佳用藥方案,改善治療效果,提高治療效率,也可作為藥品審計依據(jù)。研究結果表明,在醫(yī)療衛(wèi)生領域的疾病預防和藥物治療等方面的數(shù)據(jù)中進行數(shù)據(jù)挖掘處理和分析是一個值得重視的研究方向。
[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.
【學位授予單位】：云南大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：R319;TP311.13

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