Early identification of epilepsy surgery candidates: A multicenter, machine learning study.

Journal: Acta neurologica Scandinavica
Published Date:

Abstract

OBJECTIVES: Epilepsy surgery is underutilized. Automating the identification of potential surgical candidates may facilitate earlier intervention. Our objective was to develop site-specific machine learning (ML) algorithms to identify candidates before they undergo surgery.

Authors

  • Benjamin D Wissel
    Department of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio.
  • Hansel M Greiner
    Division of Neurology, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
  • Tracy A Glauser
    Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio.
  • John P Pestian
    Department of Pediatrics, Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center and Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA.
  • Andrew J Kemme
    Division of Emergency Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
  • Daniel Santel
    Department of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave., MLC 7024, Cincinnati, OH, 45229-3039, USA.
  • David M Ficker
    Department of Neurology and Rehabilitation Medicine, University of Cincinnati, Cincinnati, OH, USA.
  • Francesco T Mangano
    Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio.
  • Rhonda D Szczesniak
    Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio.
  • Judith W Dexheimer
    Department of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA Division of Pediatric Emergency Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.