Artificial neural networks improve early outcome prediction and risk classification in out-of-hospital cardiac arrest patients admitted to intensive care

被引：0
作者：
Jesper Johnsson
Ola Björnsson
Peder Andersson
Andreas Jakobsson
Tobias Cronberg
Gisela Lilja
Hans Friberg
Christian Hassager
Jesper Kjaergard
Matt Wise
Niklas Nielsen
Attila Frigyesi
机构：
[1] Lund University,Department of Clinical Sciences Lund, Anesthesia & Intensive Care, Helsingborg Hospital
[2] Helsingborg Hospital,Department of Anaesthesiology and Intensive Care
[3] Lund University,Centre for Mathematical Sciences, Mathematical Statistics
[4] Lund University,Department of Energy Sciences, Faculty of Engineering
[5] Lund University,Department of Clinical Sciences Lund, Anesthesia & Intensive Care, Skåne University Hospital
[6] Lund University,Department of Clinical Sciences Lund, Neurology, Skåne University Hospital
[7] Lund University,Department of Clinical Sciences Lund, Intensive and Perioperative Care, Skåne University Hospital
[8] University of Copenhagen,Department of Cardiology, The Heart Centre, Rigshospitalet University Hospital and Department of Clinical Medicine
[9] University Hospital of Wales,Department of Critical Care
来源：
Critical Care | / 24卷
关键词：
Machine learning; Artificial intelligence; Artificial neural networks; Out-of-hospital cardiac arrest; Cerebral performance category; Critical care; Intensive care; Prediction; Prognostication;
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