Predicting neurological outcome after out-of-hospital cardiac arrest with cumulative information; development and internal validation of an artificial neural network algorithm

Predicting neurological outcome after out-of-hospital cardiac arrest with cumulative information; development and internal validation of an artificial neural network algorithm

Abstract Background Prognostication of neurological outcome in patients who remain comatose after cardiac arrest resuscitation is complex. Clinical variables, as well as biomarkers of brain injury, cardiac injury, and systemic inflammation, all yield some prognostic value. We hypothesised that cumul...

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Bibliographic Details
Main Authors: Peder Andersson, Jesper Johnsson, Ola Björnsson, Tobias Cronberg, Christian Hassager, Henrik Zetterberg, Pascal Stammet, Johan Undén, Jesper Kjaergaard, Hans Friberg, Kaj Blennow, Gisela Lilja, Matt P. Wise, Josef Dankiewicz, Niklas Nielsen, Attila Frigyesi
Format: Article
Language:English
Published: BMC 2021-02-01
Series:Critical Care
Subjects:
Machine learning
Artificial intelligence
Artificial neural networks
Neural networks
Out-of-hospital cardiac arrest
Cardiac arrest
Online Access:https://doi.org/10.1186/s13054-021-03505-9

Internet

https://doi.org/10.1186/s13054-021-03505-9

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