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

被引：0
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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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