Deep learning applied to whole-brain connectome to determine seizure control after epilepsy surgery.

Journal: Epilepsia
Published Date: Aug 10, 2018

Abstract

OBJECTIVE: We evaluated whether deep learning applied to whole-brain presurgical structural connectomes could be used to predict postoperative seizure outcome more accurately than inference from clinical variables in patients with mesial temporal lobe epilepsy (TLE).

Authors

  • Ezequiel Gleichgerrcht
    Department of Neurology, Medical University of South Carolina, Charleston, SC 29425, USA.
  • Brent Munsell
    Department of Computer Science, University of North Carolina, Chapel Hill, NC 27599, USA.
  • Sonal Bhatia
    Department of Neurology, Medical University of South Carolina, Charleston, South Carolina.
  • William A Vandergrift
    Department of Neurosurgery, Medical University of South Carolina, Charleston, South Carolina.
  • Chris Rorden
    Department of Psychology, University of South Carolina, Columbia, South Carolina.
  • Carrie McDonald
    Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA.
  • Jonathan Edwards
    Department of Neurology, Medical University of South Carolina, Charleston, South Carolina.
  • Ruben Kuzniecky
    Department of Neurology, Hofstra University/Northwell, New York, NY 10075, USA.
  • Leonardo Bonilha
    Department of Neurology, Medical University of South Carolina, Charleston, SC 29425, USA.

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