Efficient use of clinical EEG data for deep learning in epilepsy.

Journal: Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Published Date: Mar 26, 2021

Abstract

OBJECTIVE: Automating detection of Interictal Epileptiform Discharges (IEDs) in electroencephalogram (EEG) recordings can reduce the time spent on visual analysis for the diagnosis of epilepsy. Deep learning has shown potential for this purpose, but the scarceness of expert annotated data creates a bottleneck in the process.

Authors

  • Catarina da Silva Lourenço
    Department of Clinical Neurophysiology, Technical Medical Centre, University of Twente, Enschede, The Netherlands.
  • Marleen C Tjepkema-Cloostermans
    Department of Clinical Neurophysiology and Neurology, Medisch Spectrum Twente, Enschede, The Netherlands. Electronic address: m.tjepkema-cloostermans@mst.nl.
  • Michel J A M van Putten
    Department of Clinical Neurophysiology, MIRA-Institute for Biomedical Technology and Technical Medicine, University of Twente & Medisch Spectrum Twente, Enschede, The Netherlands. m.j.a.m.vanputten@utwente.nl.

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