Big data in epilepsy: Clinical and research considerations. Report from the Epilepsy Big Data Task Force of the International League Against Epilepsy.

Journal: Epilepsia
PMID: 32767763

Abstract

Epilepsy is a heterogeneous condition with disparate etiologies and phenotypic and genotypic characteristics. Clinical and research aspects are accordingly varied, ranging from epidemiological to molecular, spanning clinical trials and outcomes, gene and drug discovery, imaging, electroencephalography, pathology, epilepsy surgery, digital technologies, and numerous others. Epilepsy data are collected in the terabytes and petabytes, pushing the limits of current capabilities. Modern computing firepower and advances in machine and deep learning, pioneered in other diseases, open up exciting possibilities for epilepsy too. However, without carefully designed approaches to acquiring, standardizing, curating, and making available such data, there is a risk of failure. Thus, careful construction of relevant ontologies, with intimate stakeholder inputs, provides the requisite scaffolding for more ambitious big data undertakings, such as an epilepsy data commons. In this review, we assess the clinical and research epilepsy landscapes in the big data arena, current challenges, and future directions, and make the case for a systematic approach to epilepsy big data.

Authors

  • Samden D Lhatoo
    University of Texas Health Science Center at Houston, Houston, TX 77030.
  • Neda Bernasconi
    McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, 3801 University Street, Montreal, QC, H3A2B4, Canada.
  • Ingmar Blumcke
    Institute of Neuropathology, University Hospitals, Erlangen, Germany.
  • Kees Braun
    Department of Child Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands.
  • Jeffrey Buchhalter
    Department of Neurology, St Joseph's Hospital and Medical Center, Phoenix, Arizona.
  • Spiros Denaxas
    UCL Institute of Health Informatics and Farr Institute of Health Informatics Research, London, United Kingdom.
  • Aristea Galanopoulou
    Saul Korey Department of Neurology, Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, New York.
  • Colin Josephson
    Department of Clinical Neurosciences, University of Calgary, Calgary, Canada.
  • Katja Kobow
    Institute of Neuropathology, University Hospitals, Erlangen, Germany.
  • Daniel Lowenstein
    Department of Neurology, University of California, San Francisco, San Francisco, California.
  • Philippe Ryvlin
    Department of Clinical Neurosciences, CHUV, Lausanne, Switzerland.
  • Andreas Schulze-Bonhage
  • Satya S Sahoo
    Division of Medical Informatics, School of Medicine, Case Western Reserve University, Cleveland, OH.
  • Maria Thom
    Institute of Neurology, University College London, London, UK.
  • David Thurman
    Emory University, Atlanta, Georgia.
  • Greg Worrell
    Department of Neurology, Mayo Clinic, Rochester, Minnesota.
  • Guo-Qiang Zhang
    University of Texas Health Science Center at Houston, Houston, TX 77030.
  • Samuel Wiebe
    Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.

Keywords

External Resources

Popular Topics
Recent Journals