L2G-ECG: Learning to Generate Missing Leads in ECG Signals using Adversarial Autoencoder

An electrocardiogram (ECG) is a clinically accepted record used for the diagnosis of cardiovascular diseases. The standard guideline to monitor heart health is to employ 12-lead ECG signals. Yet, in certain trauma patients or ones with physical injury, it is not possible to place electrodes at presc...

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Veröffentlicht in:	IEEE journal of biomedical and health informatics Jg. PP; S. 1 - 11
Hauptverfasser:	Srivastava, Apoorva, Sheet, Debdoot, Patra, Amit
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 09.07.2025
Schlagworte:	Adversarial learning Autoencoders Bioinformatics Convolution Deep learning Electrocardiogram Electrocardiography Electrodes Generation Generative adversarial networks Lead Limbs Missing leads Myocardium Training
ISSN:	2168-2194, 2168-2208, 2168-2208
Online-Zugang:	Volltext
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