Serial electrocardiography to detect newly emerging or aggravating cardiac pathology: a deep-learning approach.

Journal: Biomedical engineering online
Published Date: Feb 12, 2019

Abstract

BACKGROUND: Serial electrocardiography aims to contribute to electrocardiogram (ECG) diagnosis by comparing the ECG under consideration with a previously made ECG in the same individual. Here, we present a novel algorithm to construct dedicated deep-learning neural networks (NNs) that are specialized in detecting newly emerging or aggravating existing cardiac pathology in serial ECGs.

Authors

  • Agnese Sbrollini
    Cardiology Department, Leiden University Medical Center, PO Box 9600, 2300 RC, Leiden, The Netherlands.
  • Marjolein C De Jongh
    Cardiology Department, Leiden University Medical Center, PO Box 9600, 2300 RC, Leiden, The Netherlands.
  • C Cato Ter Haar
    Cardiology Department, Leiden University Medical Center, PO Box 9600, 2300 RC, Leiden, The Netherlands.
  • Roderick W Treskes
    Cardiology Department, Leiden University Medical Center, PO Box 9600, 2300 RC, Leiden, The Netherlands.
  • Sumche Man
    Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands.
  • Laura Burattini
    Information Engineering Department, Università Politecnica delle Marche, Via Brecce Bianche, 12, 60121, Ancona, Italy.
  • Cees A Swenne
    Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands. Electronic address: c.a.swenne@lumc.nl.

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