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A Simple and Effective Method for Detecting Myocardial Infarction Based on Deep Convolutional Neural Network 期刊论文

编号：

b4a9bb2d-29fd-41a1-8313-c68243f408c6
作者：

Liu, Na#^[1]Wang, Ludi^[1];Chang, Qing^[2];Xing, Ying^[1];Zhou, Xiaoguang*^[1]
语种：

英文
期刊：

JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS ISSN：2156-7018 2018 年 8 卷 7 期 (1508 - 1512) ; SEP
收录：
关键词：

Electrocardiogram (ECG) Myocardial Infarction (MI) Deep Convolution Neural Network (CNN) MI Detection
摘要：

Myocardial infarction (MI) is the main cause of sudden death in patients with cardiovascular diseases (CVD), thus timely detection of myocardial infarction is crucial for saving patients' lives. This paper presents an algorithm based on deep convolution neural network (CNN) to detect myocardial infarction, using electrocardiogram (ECG) signal from lead II. The algorithm proposed in this paper uses neither manual feature extraction nor feature selection, and instead of performing heartbeat segmentation, the method takes 3 second ECG signal segments as input. For our experiments, we conduct two datasets of denoised ECG set and original ECG set to corroborate the robustness of the algorithm to noise in ECG signal. We evaluate the model by a 10-fold cross-validation on the PTB database and achieve the state-of-the-art result: accuracy = 99.34%, sensitivity = 99.79% and specificity = 97.44% for the denoised ECG signal, and accuracy = 98.59%, sensitivity = 99.53% and specificity = 94.50% for the raw ECG signal.
推荐引用方式
GB/T 7714：

Liu Na,Wang Ludi,Chang Qing, et al. A Simple and Effective Method for Detecting Myocardial Infarction Based on Deep Convolutional Neural Network [J].JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS,2018,8(7):1508-1512.
APA：

Liu Na,Wang Ludi,Chang Qing,Xing Ying,&Zhou Xiaoguang.(2018).A Simple and Effective Method for Detecting Myocardial Infarction Based on Deep Convolutional Neural Network .JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS,8(7):1508-1512.
MLA：

Liu Na, et al. "A Simple and Effective Method for Detecting Myocardial Infarction Based on Deep Convolutional Neural Network" .JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS 8,7(2018):1508-1512.

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