Quantitative EEG reactivity and machine learning for prognostication in hypoxic-ischemic brain injury-Reference-Cited by-同舟云学术

Quantitative EEG reactivity and machine learning for prognostication in hypoxic-ischemic brain injury

Published:2019-10 Issue:10 Volume:130 Page:1908-1916
ISSN:1388-2457
Container-title:Clinical Neurophysiology
language:en
Short-container-title:Clinical Neurophysiology

Author:

Amorim Edilberto,van der Stoel Michelle,Nagaraj Sunil B.,Ghassemi Mohammad M.,Jing Jin,O'Reilly Una-May,Scirica Benjamin M.,Lee Jong Woo,Cash Sydney S.,Westover M. Brandon

Funder

Neurocritical Care Society

American Heart Association

MIT

Andrew David Heitman Neuroendovascular Research Fund

Rappaport Foundation

NIH

Salerno foundation

Publisher

Elsevier BV

Subject

Physiology (medical),Neurology (clinical),Neurology,Sensory Systems

Reference28 articles.

1. Stimulus-induced rhythmic, periodic or ictal discharges (SIRPIDs) in comatose survivors of cardiac arrest: characteristics and prognostic value;Alvarez;Clin Neurophysiol,2013

2. Dynamic quantitative EEG signatures predict outcome in cardiac arrest;Amorim;Neurocrit Care,2016

3. EEG reactivity evaluation practices for adult and pediatric hypoxic-ischemic coma prognostication in North America;Amorim;J Clin Neurophys,2018

4. Malignant EEG patterns in cardiac arrest patients treated with targeted temperature management who survive to hospital discharge;Amorim;Resuscitation,2015

5. Continuous EEG monitoring enhances multimodal outcome prediction in hypoxic-ischemic brain injury;Amorim;Resuscitation,2016

Cited by 63 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. EEG Reactivity in Neurologic Prognostication in Post-Cardiac Arrest Patients: A Narrative Review;Resuscitation;2024-09

2. EEG for good outcome prediction after cardiac arrest: A multicentre cohort study;Resuscitation;2024-09

3. Quantitative EEG reactivity induced by electrical stimulation predicts good outcome in comatose patients after cardiac arrest;Annals of Intensive Care;2024-06-27

4. Methods of Evaluating EEG Reactivity in Adult Intensive Care Units: A Review;Journal of Clinical Neurophysiology;2024-06-10

5. Prediction of mild cognitive impairment using EEG signal and BiLSTM network;Machine Learning: Science and Technology;2024-05-03