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Electrocardiogram Delineation Using Deep Neural Networks
Max Haberbusch, Lisa A. Bernardo, Laura Galassi, Calogero M. Oddo, Francesco Moscato
117 - 118
10.3233/SHTI220356
Research Article
Studies in Health Technology and Informatics
Volume 293: dHealth 2022
Abstract

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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