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Prediction of heart disease using neural network

机译:使用神经网络预测心脏病

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摘要

Heart disease is a deadly disease that large population of people around the world suffers from. When considering death rates and large number of people who suffers from heart disease, it is revealed how important early diagnosis of heart disease. Traditional way of diagnosis is not sufficient for such an illness. Developing a medical diagnosis system based on machine learning for prediction of heart disease provides more accurate diagnosis than traditional way. In this paper, a heart disease prediction system which uses artificial neural network backpropagation algorithm is proposed. 13 clinical features were used as input for the neural network and then the neural network was trained with backpropagation algorithm to predict absence or presence of heart disease with accuracy of 95%.
机译:心脏病是一种致命的疾病,全世界许多人都患有这种疾病。当考虑到死亡率和大量患有心脏病的人时,揭示了心脏病的早期诊断是多么重要。传统的诊断方法不足以治疗这种疾病。开发基于机器学习的医学诊断系统以预测心脏病,比传统方法提供了更准确的诊断。本文提出了一种基于人工神经网络反向传播算法的心脏病预测系统。将13种临床特征用作神经网络的输入,然后使用反向传播算法对神经网络进行训练,以预测是否存在心脏病,其准确性为95%。

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