Generalizability of electroencephalographic interpretation using artificial intelligence: An external validation study.

Journal: Epilepsia
Published Date: Aug 14, 2024

Abstract

OBJECTIVE: The automated interpretation of clinical electroencephalograms (EEGs) using artificial intelligence (AI) holds the potential to bridge the treatment gap in resource-limited settings and reduce the workload at specialized centers. However, to facilitate broad clinical implementation, it is essential to establish generalizability across diverse patient populations and equipment. We assessed whether SCORE-AI demonstrates diagnostic accuracy comparable to that of experts when applied to a geographically different patient population, recorded with distinct EEG equipment and technical settings.

Authors

  • Daniel Mansilla
    Analytical Neurophysiology Lab, Montreal Neurological Institute and Hospital, Montreal, Quebec, Canada.
  • Jesper Tveit
    Holberg EEG, Bergen, Norway.
  • Harald Aurlien
    Holberg EEG, Bergen, Norway.
  • Tamir Avigdor
    Analytical Neurophysiology Lab, Montreal Neurological Institute and Hospital, Montreal, Quebec, Canada.
  • Victoria Ros-Castello
    Epilepsy Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain.
  • Alyssa Ho
    Department of Neurology, Duke University Medical Center, Durham, North Carolina, USA.
  • Chifaou Abdallah
    Analytical Neurophysiology Lab, Montreal Neurological Institute and Hospital, Montreal, Quebec, Canada.
  • Jean Gotman
    Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada.
  • Sándor Beniczky
    Department of Clinical Neurophysiology, Aarhus University Hospital and Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; Department of Clinical Neurophysiology, Danish Epilepsy Centre, Dianalund, Denmark. Electronic address: sbz@filadelfia.dk.
  • Birgit Frauscher
    Montreal Neurological Hospital, McGill University, 3801 Rue University, Montreal, QC H3A 2B4, Quebec, Canada; Department of Neurology, Duke University Medical School and Department of Biomedical Engineering, Pratt School of Engineering, 2424 Erwin Road, Durham, NC, 27705, USA. Electronic address: birgit.frauscher@duke.edu.

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