Machine Learning Techniques for the Detection of Shockable Rhythms in Automated External Defibrillators. - Wikidata - wikimedia - TriplyDB

Machine Learning Techniques for the Detection of Shockable Rhythms in Automated External Defibrillators.

Machine Learning Techniques for the Detection of Shockable Rhythms in Automated External Defibrillators.

http://www.wikidata.org/entity/Q37115401

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Ventricular fibrillation waveform measures combined with prior shock outcome predict defibrillation success during cardiopulmonary resuscitation.

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Machine Learning Techniques for the Detection of Shockable Rhythms in Automated External Defibrillators.

http://www.wikidata.org/entity/Q37115401

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article científic

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article scientifique

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articolo scientifico

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artigo científico

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bilimsel makale

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scientific article published on 21 July 2016

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vedecký článok

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vetenskaplig artikel

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videnskabelig artikel

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vědecký článek

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name

Machine Learning Techniques fo ...... mated External Defibrillators.

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Machine Learning Techniques fo ...... mated External Defibrillators.

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Machine Learning Techniques fo ...... mated External Defibrillators.

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Machine Learning Techniques fo ...... mated External Defibrillators.

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JOURNAL.PONE.0159654

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Machine Learning Techniques fo ...... mated External Defibrillators.

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Eduardo Morgado

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Felipe Alonso-Atienza

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Jo Kramer-Johansen

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Lars Wik

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Trygve Eftestøl

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P2860

Reliability of old and new ventricular fibrillation detection algorithms for automated external defibrillators.

Sample entropy analysis of neonatal heart rate variability.

Logarithm of the absolute correlations of the ECG waveform estimates duration of ventricular fibrillation and predicts successful defibrillation.

Sequential algorithm for life threatening cardiac pathologies detection based on mean signal strength and EMD functions.

Public-access defibrillation and survival after out-of-hospital cardiac arrest.

Quality of out-of-hospital cardiopulmonary resuscitation with real time automated feedback: a prospective interventional study.

Perishock pause: an independent predictor of survival from out-of-hospital shockable cardiac arrest.

Out-of-hospital cardiac arrest survival improving over time: Results from the Resuscitation Outcomes Consortium (ROC).

The spectrum of epidemiology underlying sudden cardiac death.

Pulseless electrical activity in cardiac arrest: electrocardiographic presentations and management considerations based on the electrocardiogram.

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e0159654

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scholarly article

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10.1371/JOURNAL.PONE.0159654

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7

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Elisabete Aramendi

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2016-07-21T00:00:00Z

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27441719

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machine learning

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4956226

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