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Sample entropy as a shock outcome predictor during basis life support

descriptionPublicationkeyboard_double_arrow_right Article 01 Sep 2015Publisher:IEEEJournal:2015 Computing in Cardiology Conference (CinC)
Authors: Beatriz Chicote; Unai Irusta; Elisabete Aramendi; Daniel Alonso; Carlos Jover; Carlos Corcuera;

doi: 10.1109/cic.2015.7410971

Sample entropy as a shock outcome predictor during basis life support

Abstract

Optimizing defibrillation times may improve survival from ventricular fibrillation (VF) cardiac arrest. VF waveform analysis is one of the best non-invasive decision tools for shock outcome prediction. This study introduces a VF-waveform feature based on the computation of the sample entropy (SmpEnt) for shock outcome prediction.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
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