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Predictions in Heart Disease Using Techniques of Data Mining

机译:利用数据挖掘技术预测心脏病

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As huge amount of information is produced in medical associations (healing facilities, therapeutic focuses) yet this information is not properly utilized. The health care system is "data rich" however "knowledge poor". There is an absence of successful analysis methods to find connections and patterns in health care data. Data mining methods can help as remedy in this circumstance. For this reason, different data mining techniques can be utilized. The paper intends to give details about various techniques of knowledge abstraction by using data mining methods that are being used in today's research for prediction of heart disease. In this paper, data mining methods namely, Naive Bayes, Neural network, Decision tree algorithm are analyzed on medical data sets using algorithms.
机译:由于在医疗协会中产生了大量信息(治疗设施,治疗焦点)尚未正确使用此信息。医疗保健系统是“数据丰富”但“知识差”。没有成功的分析方法来查找医疗保健数据中的连接和模式。数据挖掘方法可以帮助在这种情况下作为补救措施。因此,可以使用不同的数据挖掘技术。本文旨在通过使用在当今的心脏病预测中使用的数据挖掘方法提供有关各种知识抽象技术的细节。在本文中,数据挖掘方法即Naive贝叶斯,神经网络,决策树算法使用算法分析了医学数据集。

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