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首页> 外文期刊>Procedia Computer Science >Performance Analysis of Support Vector Machine and Neural Networks in Detection of Myocardial Infarction
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Performance Analysis of Support Vector Machine and Neural Networks in Detection of Myocardial Infarction

机译:支持向量机和神经网络在心肌梗死检测中的性能分析

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摘要

One of the most common form of cardiac abnormality is Myocardial Infarction (heart attack) arises when the artery connecting the heart is blocked and there is no sufficient blood or oxygen, which makes the cells present in that region of the heart to die. This paper aims to process and classify an ECG signal as healthy subject or subject diagnosed with Myocardial Infarction (MI) using Artificial Neural Networks (ANN) and SVM (Support Vector Machine). LIBSVM 1 is utilized for the classification with SVM and backpropogation artificial neural networks with varying hidden layers and nodes are also implemented for performance analysis.
机译:心脏异常的最常见形式之一是心肌梗塞(心脏病发作),发生在连接心脏的动脉被阻塞并且没有足够的血液或氧气时,心脏区域中的细胞死亡。本文旨在使用人工神经网络(ANN)和SVM(支持向量机)将ECG信号处理为健康受试者或诊断为心肌梗塞(MI)的受试者,并将其分类。 LIBSVM 1用于通过SVM进行分类,反向传播人工神经网络具有变化的隐藏层,并且还实施了节点进行性能分析。

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