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Found 2 papers, 1 papers with code
A deep convolutional neural network model to classify heartbeats
The CNN was trained using the augmented data and achieved an accuracy of 94. 03% and 93. 47% in the diagnostic classification of heartbeats in original and noise free ECGs, respectively.
Application of deep convolutional neural network for automated detection of myocardial infarction using ecg signals
In this study, we implemented a convolutional neural network (CNN) algorithm for the automated detection of a normal and MI ECG beats (with noise and without noise).
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