Unsupervised Learning of Spatiotemporal Interictal Discharges in Focal Epilepsy.

Journal: Neurosurgery
Published Date: Oct 1, 2018

Abstract

BACKGROUND: Interictal epileptiform discharges are an important biomarker for localization of focal epilepsy, especially in patients who undergo chronic intracranial monitoring. Manual detection of these pathophysiological events is cumbersome, but is still superior to current rule-based approaches in most automated algorithms.

Authors

  • Maxime O Baud
    Department of Neurological surgery, University of California, San Francisco, California.
  • Jonathan K Kleen
    Department of Neurology, University of California, San Francisco, California.
  • Gopala K Anumanchipalli
    Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94143, USA.
  • Liberty S Hamilton
    Department of Neurological surgery, University of California, San Francisco, California.
  • Yee-Leng Tan
    Department of Neurology, University of California, San Francisco, San Francisco, CA, USA; Department of Neurology, National Neuroscience Institute, Singapore. Electronic address: tan.yee.leng.neuro@singhealth.com.sg.
  • Robert Knowlton
    Department of Neurology, University of California, San Francisco, San Francisco, CA, USA. Electronic address: robert.knowlton@ucsf.edu.
  • Edward F Chang
    Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94143, USA. Electronic address: edward.chang@ucsf.edu.

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