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Paper Details

Deep active learning for Interictal Ictal Injury Continuum EEG patterns.
J Neurosci Methods
8
2021
Dense, HCSBBQ, Ictal Injury, Seizures, critically ill, patient, patients
Cluster Analysis, Electroencephalography, Humans, Neural Networks, Computer, Seizures
Author NameAffiliation
Wendong GeMassachusetts General Hospital, United States Harvard Medical School
Jin JingMassachusetts General Hospital, United States Harvard Medical School
Sungtae AnGeorgia Institute of Technology, College of Computing
Aline HerlopianYale University
Marcus C NgUniversity of Manitoba
Aaron F StruckUniversity of Wisconsin Madison Department of Neurology
Brian AppavuUniversity of Arizona College of Medicine
Emily L JohnsonJohns Hopkins School of Medicine
Gamaleldin OsmanHenry Ford Hospital
Hiba ArifEmory University School of Medicine
Ioannis KarakisEmory University School of Medicine
Jennifer A KimYale University
Jonathan J HalfordMedical University of South Carolina
Monica B DhakarEmory University School of Medicine
Rani A SarkisBrigham and Women's Hospital
Christa B SwisherDuke University Hospital
Sarah SchmittMedical University of South Carolina
Jong Woo LeeBrigham and Women's Hospital
Mohammad TabaeizadehBaylor College of Medicine
Andres RodriguezEmory University School of Medicine
Nicolas GaspardUniversite Libre de Bruxelles, Hopital Erasme and Yale University
Emily J GilmoreYale University, Yale New Haven Hospital
Susan T HermanBarrow Neurological Institute
Peter W KaplanJohns Hopkins University
Jay PathmanathanUniversity of Pennsylvania
Shenda HongGeorgia Institute of Technology, College of Computing
Eric S RosenthalMassachusetts General Hospital, United States Harvard Medical School
Sahar F ZafarMassachusetts General Hospital, United States Harvard Medical School
Jimeng SunUniversity of Illinois at Urbana-Champaign, College of Computing
Michael B WestoverMassachusetts General Hospital, United States Harvard Medical School
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