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Cardiac Arrhythmia Diagnosis System from Electrocardiogram Signal using Machine Learning Approach

机译:基于机器学习方法的心电图信号心律失常诊断系统

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People nowadays come cross lot of life threatening diseases. One of the crucial diseases is cardiac disease. Cardiac arrhythmia is a disorder which needs timely diagnosis for avoiding sudden cardiac arrest. In Arrhythmia, the heartbeat is too irregular, too slow, or too fast. The Cardiac diseases are monitored using electrocardiogram (ECG). The major objective of this paper is to discriminate between the normal and diseased persons using machine learning approach. The Cardiac Arrhythmia Diagnosis system involves the following processes such as feature extraction, feature selection and classification. Feed forward Neural Network is proposed in this work and results are compared with support vector machine.
机译:如今人们遇到许多威胁生命的疾病。关键疾病之一是心脏病。心脏心律失常是一种需要及时诊断的疾病,以避免心脏骤停。在心律不齐中,心跳太不规则,太慢或太快。使用心电图(ECG)监测心脏疾病。本文的主要目的是使用机器学习方法来区分正常人和疾病人。心律失常诊断系统涉及以下过程,例如特征提取,特征选择和分类。提出了前馈神经网络,并将结果与​​支持向量机进行了比较。

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