Heart disease prediction using data mining techniques

Abhishek Rairikar, V. Kulkarni, V. Sabale, H. Kale, A. Lamgunde
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引用次数: 148

Abstract

The healthcare industry collects large amounts of Healthcare data, but unfortunately not all the data are mined which is required for discovering hidden patterns and effective decision making. We propose efficient genetic algorithm with the back propagation technique approach for heart disease prediction. This paper has analyzed prediction systems for Heart disease using more number of input attributes. The System uses medical terms such as Gender, blood pressure, cholesterol like13 attributes to predict the likelihood of patient getting a Heart disease.
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使用数据挖掘技术预测心脏病
医疗保健行业收集了大量的医疗保健数据,但不幸的是,并不是所有的数据都被挖掘出来,而这些数据是发现隐藏模式和有效决策所必需的。提出了一种基于反向传播的遗传算法的心脏病预测方法。本文分析了使用更多输入属性的心脏病预测系统。该系统使用医学术语,如性别、血压、胆固醇等13个属性来预测患者患心脏病的可能性。
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