New Method of Early RRMS Diagnosis Using OCT-Assessed Structural Retinal Data and Explainable Artificial Intelligence.

Journal: Translational vision science & technology
PMID: 39928305

Abstract

PURPOSE: The purpose of this study was to provide the development of a method to classify optical coherence tomography (OCT)-assessed retinal data in the context of automatic diagnosis of early-stage multiple sclerosis (MS) with decision explanation.

Authors

  • Miguel Ortiz
    School of Physics, University of Melbourne, Victoria, Australia.
  • Ana Pueyo
    Department of Ophthalmology, Miguel Servet University Hospital, Zaragoza, Spain.
  • Francisco J Dongil
    Biomedical Engineering Group, Department of Electronics, University of Alcalá, Alcalá de Henares, Spain.
  • Luciano Boquete
    Biomedical Engineering Group, Department of Electronics, University of Alcalá, 28801 Alcalá de Henares, Spain.
  • Eva M Sánchez-Morla
    Institute of Psychiatry and Mental Health, Gregorio Marañón University Hospital, IiSGM, Madrid, Spain.
  • Rafael Barea
    Biomedical Engineering Group, Department of Electronics, University of Alcalá, Alcalá de Henares, Spain.
  • Juan M Miguel-Jimenez
    Biomedical Engineering Group, Department of Electronics, University of Alcalá, Alcalá de Henares, Spain.
  • Almudena López-Dorado
    Biomedical Engineering Group, Department of Electronics, University of Alcalá, Alcalá de Henares, Spain.
  • Elisa Vilades
    Department of Ophthalmology, Miguel Servet University Hospital, Zaragoza, Spain.
  • María J Rodrigo
    Department of Ophthalmology, Miguel Servet University Hospital, Zaragoza, Spain.
  • Beatriz Cordon
    Department of Ophthalmology, Miguel Servet University Hospital, Zaragoza, Spain.
  • Elena García-Martín

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