Neural networks to estimate multiple sclerosis disability and predict progression using routinely collected healthcare data.

Journal: Multiple sclerosis (Houndmills, Basingstoke, England)
Published Date: Jul 3, 2025

Abstract

BACKGROUND AND OBJECTIVES: Multiple sclerosis (MS)-related disability is conventionally measured using the Expanded Disability Status Scale (EDSS), which requires neurological examination and is generally embedded in clinical records, making it unavailable in administrative datasets. This limits its utility for population-level estimates and healthcare planning. This study aims to use routinely collected healthcare data to fill this gap.

Authors

  • Giuseppina Affinito
    Department of Public Health, University "Federico II" of Naples, Naples, Italy.
  • Marcello Moccia
    Department of Molecular Medicine and Medical Biotechnology, Federico II University of Naples, Naples, Italy.
  • Roberta Lanzillo
    Department of Neurosciences, Reproductive Sciences and Odontostomatology, University of Naples Federico II, Naples, Italy.
  • Ruth Ann Marrie
    Department of Internal Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada; Department of Community Health Sciences, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada. Electronic address: rmarrie@hsc.mb.ca.
  • Jeremy Chataway
    Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK.
  • Vincenzo Brescia Morra
    Department of Neuroscience, Reproductive Science and Odontostomatology, University of Naples Federico II, Naples, Italy.
  • Raffaele Palladino
    Department of Public Health, University "Federico II" of Naples, Naples, Italy.

Keywords

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