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Utilization of the Apriori Data Mining method in a research software with electronic protocol in Enteral Nutrition

机译:肠内营养中电子协议的研究软件在研究软件中利用APRiori数据挖掘方法

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The aims this paper is to display the Apriori Data Mining Method results implanted in SINPE(c) (Electronic Protocols Integrated System) in an Enteral Nutrition research. We developed the data mining in the SINPE and later the items Body Mass Index (BMI or IMC) and Enteral diet were selected from the database of the Homecare Enteral Nutrition Research, The parameters used were 10% support and 50% confidence. The Apriori generated a rule showing that patients with BMI < 22 kg/m~2 implied the intake of a homemade diet. The application of the Apriori Data Mining Method shows itself more dynamic, allowing the data intersection, and helping on decisions and on the elaboration of diagnostics as well as on diet prescriptions, checking the possible relationships between the analyzed items.
机译:本文的目的是在肠内营养研究中显示植入SINPE(C)(C)(电子协议综合系统)中的APRiori数据挖掘方法结果。我们开发了SINPE中的数据挖掘,后来项目体重指数(BMI或IMC)和肠内饮食选自Homecare肠内营养研究的数据库,所使用的参数是10%的支持和50%的信心。 Apriori产生了一个规则,显示BMI <22 kg / m〜2的患者暗示自制饮食的摄入量。 APRiori数据挖掘方法的应用显示了更具动态的,允许数据交叉,并帮助决策以及在诊断和饮食处方的阐述,检查分析物品之间的可能关系。

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