Development of a natural language processing algorithm to extract seizure types and frequencies from the electronic health record.

Journal: Seizure
Published Date:

Abstract

OBJECTIVE: To develop a natural language processing (NLP) algorithm to abstract seizure types and frequencies from electronic health records (EHR).

Authors

  • Barbara M Decker
    Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States; Department of Neurological Sciences, University of Vermont Medical Center, Burlington, VT, United States. Electronic address: Barbara.decker@uvmhealth.org.
  • Alexandra Turco
    Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States.
  • Jian Xu
    Department of Cardiology, Lishui Central Hospital and the Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, China.
  • Samuel W Terman
  • Nikitha Kosaraju
    Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States.
  • Alisha Jamil
    Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States.
  • Kathryn A Davis
    Penn Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104; Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA 19104.
  • Brian Litt
    Penn Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA, United States of America.
  • Colin A Ellis
    Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Pouya Khankhanian
    MS Genetics, Department of Neurology, School of Medicine, University of California San Francisco (UCSF), San Francisco, CA, USA/Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA, USA.
  • Chloe E Hill
    Department of Neurology, University of Michigan, Ann Arbor, MI, United States.