Predicting neurological outcome from electroencephalogram dynamics in comatose patients after cardiac arrest with deep learning

WL Zheng, E Amorim, J Jing, O Wu… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Objective: Most cardiac arrest patients who are successfully resuscitated are initially
comatose due to hypoxic-ischemic brain injury. Quantitative electroencephalography (EEG) …
被引用次数：25 相关文章

Predicting Neurological Outcome From Electroencephalogram Dynamics in Comatose Patients After Cardiac Arrest With Deep Learning

WL Zheng, E Amorim, J Jing, O Wu… - … transactions on bio …, 2022 - pubmed.ncbi.nlm.nih.gov
Objective Most cardiac arrest patients who are successfully resuscitated are initially
comatose due to hypoxic-ischemic brain injury. Quantitative electroencephalography (EEG) …

Predicting Neurological Outcome from Electroencephalogram Dynamics in Comatose Patients after Cardiac Arrest with Deep Learning

WL Zheng, E Amorim, J Jing, O Wu… - IEEE transactions on …, 2022 - research.utwente.nl
Objective: Most cardiac arrest patients who are successfully resuscitated are initially
comatose due to hypoxic-ischemic brain injury. Quantitative electroencephalography (EEG) …

[引用][C] Predicting Neurological Outcome from Electroencephalogram Dynamics in Comatose Patients after Cardiac Arrest with Deep Learning

WL Zheng, E Amorim, J Jing, O Wu… - IEEE transactions on …, 2021 - difusion.ulb.ac.be
[HTML] nih.gov

[HTML][HTML] Predicting Neurological Outcome from Electroencephalogram Dynamics in Comatose Patients after Cardiac Arrest with Deep Learning

WL Zheng, E Amorim, J Jing, O Wu… - IEEE transactions on …, 2022 - ncbi.nlm.nih.gov
Objective: Most cardiac arrest patients who are successfully resuscitated are initially
comatose due to hypoxic-ischemic brain injury. Quantitative electroencephalography (EEG) …
[PDF] github.io

[PDF][PDF] Predicting Neurological Outcome from Electroencephalogram Dynamics in Comatose Patients after Cardiac Arrest with Deep Learning

WL Zheng, E Amorim, J Jing, O Wu, M Ghassemi… - weilongzheng.github.io
Objective: Most cardiac arrest patients who 1 are successfully resuscitated are initially
comatose due 2 to hypoxic-ischemic brain injury. Quantitative electroen-3 cephalography …
[PDF] ulb.ac.be

[PDF][PDF] Predicting Neurological Outcome from Electroencephalogram Dynamics in Comatose Patients after Cardiac Arrest with Deep Learning

WL Zheng, E Amorim, J Jing, O Wu… - IEEE Trans Biomed …, 2022 - dipot.ulb.ac.be
Objective: Most cardiac arrest patients who are successfully resuscitated are initially
comatose due to hypoxic-ischemic brain injury. Quantitative electroencephalography (EEG) …
[PDF] utwente.nl

[PDF][PDF] Predicting Neurological Outcome from Electroencephalogram Dynamics in Comatose Patients after Cardiac Arrest with Deep Learning

WL Zheng, E Amorim, J Jing, O Wu, M Ghassemi… - ris.utwente.nl
Objective: Most cardiac arrest patients who 1 are successfully resuscitated are initially
comatose due 2 to hypoxic-ischemic brain injury. Quantitative electroen-3 cephalography …

Predicting Neurological Outcome From Electroencephalogram Dynamics in Comatose Patients After Cardiac Arrest With Deep Learning.

WL Zheng, E Amorim, J Jing, O Wu… - IEEE Transactions on …, 2022 - europepmc.org
Objective Most cardiac arrest patients who are successfully resuscitated are initially
comatose due to hypoxic-ischemic brain injury. Quantitative electroencephalography (EEG) …