用密集神经网络预测心脏病

Akansha Singh, Anamika Jain
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引用次数: 0

摘要

由于人类的生活方式,心脏病在人类中很常见。如果不及时治疗,就会危及生命。因此,心脏病的早期检测变得非常重要。许多研究人员对心脏病的预测进行了大量的研究。为了最大限度地降低患者的生命损失风险,我们提出了一种基于人工神经网络的心脏病早期预测方法。该方法在公开可用的UCI数据集上进行了测试。该方法的准确率达到96.09%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction of Heart Disease using Dense Neural Network
Heart disease are very common in humans because of their life style. It become life threatening when do not treated on time. So the early detection of heart disease has become very important. Many researchers have done a lot of research on the prediction of the heart disease. To minimize the risk of loosing life, we have proposed a Artificial neural network based method that can predict the heart disease in the early stages. The proposed method is tested over the publicly available UCI dataset. We have achieved 96.09% accuracy with the proposed method.
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