Artificial intelligence in epilepsy - applications and pathways to the clinic.

Journal: Nature reviews. Neurology
Published Date:

Abstract

Artificial intelligence (AI) is rapidly transforming health care, and its applications in epilepsy have increased exponentially over the past decade. Integration of AI into epilepsy management promises to revolutionize the diagnosis and treatment of this complex disorder. However, translation of AI into neurology clinical practice has not yet been successful, emphasizing the need to consider progress to date and assess challenges and limitations of AI. In this Review, we provide an overview of AI applications that have been developed in epilepsy using a variety of data modalities: neuroimaging, electroencephalography, electronic health records, medical devices and multimodal data integration. For each, we consider potential applications, including seizure detection and prediction, seizure lateralization, localization of the seizure-onset zone and assessment for surgical or neurostimulation interventions, and review the performance of AI tools developed to date. We also discuss methodological considerations and challenges that must be addressed to successfully integrate AI into clinical practice. Our goal is to provide an overview of the current state of the field and provide guidance for leveraging AI in future to improve management of epilepsy.

Authors

  • Alfredo Lucas
    Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Andrew Revell
    Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • 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.