Background: In recent years, there has been a rising interest in the application of deep neural networks (DNN) for the delineation of the electrocardiogram (ECG).
Objectives: A variety of DNN architectures has been investigated in a 5-fold cross-validation approach.
Results: The best performing network achieved 100% sensitivity and >97% positive predictive value for all ECG waves.
Conclusion: Our DNN could achieve similar classification performance as other DNN approaches described in the literature at a reduced computational cost.
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| http://dx.doi.org/10.3233/SHTI220356 | DOI Listing |
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