Computationally Efficient Early Prognosis of the Outcome of Comatose Cardiac Arrest Survivors Using Slow-Wave Activity Features in EEG

This study, part of 'Predicting Neurological Recovery from Coma After Cardiac Arrest: The George B. Moody PhysioNet Challenge 2023', evaluated a computationally efficient method in predicting cardiac arrest (CA) survivors' prognoses using electroencephalography (EEG) recordings of a d...

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Bibliographic Details

Published in:	Computing in cardiology Vol. 50; pp. 1 - 4
Main Authors:	Salminen, Miikka, Partala, Juha, Vayrynen, Eero, Kortelainen, Jukka
Format:	Conference Proceeding
Language:	English
Published:	CinC 01.10.2023
Subjects:	Cardiac arrest Computational efficiency Electroencephalography Recording Root mean square Training Training data
ISSN:	2325-887X
Online Access:	Get full text
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