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

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...

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Bibliographic Details
Published in:	Biomedical engineering online Vol. 18; no. 1; pp. 15 - 17
Main Authors:	Sbrollini, Agnese, De Jongh, Marjolein C., Ter Haar, C. Cato, Treskes, Roderick W., Man, Sumche, Burattini, Laura, Swenne, Cees A.
Format:	Journal Article
Language:	English
Published:	London BioMed Central 12.02.2019 Springer Nature B.V BMC
Subjects:	Acute coronary syndromes Algorithms Automation Biomaterials Biomedical Engineering and Bioengineering BioMedical Engineering and the Heart Biomedical Engineering/Biotechnology Biotechnology Change detection Complexity Congestive heart failure Constructive algorithm Deep learning Echocardiography EKG Electrocardiography Engineering Heart failure Heart rate Infarction Integrals Ischemia Myocardial infarction Neural networks Optimization Pathology Patients Physiology Serial electrocardiography Vectorcardiography Ventricle Deep learning Constructive algorithm Vectorcardiography Serial electrocardiography Neural networks
ISSN:	1475-925X, 1475-925X
Online Access:	Get full text
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