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Paper Details

Predicting neurological outcome in comatose patients after cardiac arrest with multiscale deep neural networks.
Resuscitation
11
2021
LSTM, cardiac arrest, cardiac arrest coma, coma, comatose, patients
Coma, Electroencephalography, Heart Arrest, Humans, Neural Networks, Computer, Prognosis, Prospective Studies
Author NameAffiliation
Wei-Long ZhengMassachusetts General Hospital, Harvard Medical School
Edilberto AmorimUniversity of California san francisco
Jin JingMassachusetts General Hospital, Harvard Medical School
Wendong GeMassachusetts General Hospital, Harvard Medical School
Shenda HongUniversity of Illinois at Urbana Champaign
Ona WuMassachusetts General Hospital, Harvard Medical School
Mohammad M GhassemiMichigan State University, Massachusetts Institute of Technology
Jong Woo LeeBrigham and Women's Hospital
Adithya SivarajuYale School of Medicine
Trudy D PangBeth Israel Deaconess Medical Center
Susan T HermanBarrow Neurological Institute
Nicolas GaspardUniversite Libre de Bruxelles
Barry J RuijterUniversity of Twente
Jimeng SunUniversity of Illinois at Urbana Champaign
Marleen C Tjepkema-CloostermansDepartments of Neurology and Clinical Neurophysiology, Rijnstate Hospital
Jeannette HofmeijerUniversity of Twente, Rijnstate Hospital
Michel J A M van PuttenUniversity of Twente, the Netherlands Departments of Neurology and Clinical Neurophysiology
Michael B WestoverMassachusetts General Hospital, Harvard Medical School
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