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Mixed convolutional and long short-term memory network for the detection of lethal ventricular arrhy...

Mixed convolutional and long short-term memory network for the detection of lethal ventricular arrhy...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_2227830307

Mixed convolutional and long short-term memory network for the detection of lethal ventricular arrhythmia

About this item

Full title

Mixed convolutional and long short-term memory network for the detection of lethal ventricular arrhythmia

Publisher

United States: Public Library of Science

Journal title

PloS one, 2019-05, Vol.14 (5), p.e0216756-e0216756

Language

English

Formats

Publication information

Publisher

United States: Public Library of Science

More information

Scope and Contents

Contents

Early defibrillation by an automated external defibrillator (AED) is key for the survival of out-of-hospital cardiac arrest (OHCA) patients. ECG feature extraction and machine learning have been successfully used to detect ventricular fibrillation (VF) in AED shock decision algorithms. Recently, deep learning architectures based on 1D Convolutional...

Alternative Titles

Full title

Mixed convolutional and long short-term memory network for the detection of lethal ventricular arrhythmia

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_plos_journals_2227830307

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_2227830307

Other Identifiers

ISSN

1932-6203

E-ISSN

1932-6203

DOI

10.1371/journal.pone.0216756

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