Suitability of machine learning for atrophy and fibrosis development in neovascular age-related macular degeneration.

Journal: Acta ophthalmologica
PMID:

Abstract

PURPOSE: To assess the suitability of machine learning (ML) techniques in predicting the development of fibrosis and atrophy in patients with neovascular age-related macular degeneration (nAMD), receiving anti-VEGF treatment over a 36-month period.

Authors

  • Jesús de la Fuente
    TECNUN School of Engineering, University of Navarra, Navarra, Spain.
  • Sara Llorente-González
    Retinal Pathologies and New Therapies Group, Experimental Ophthalmology Laboratory, Department of Ophthalmology, Clinica Universidad de Navarra, Pamplona, Spain.
  • Patricia Fernandez-Robredo
    Retinal Pathologies and New Therapies Group, Experimental Ophthalmology Laboratory, Department of Ophthalmology, Clinica Universidad de Navarra, Pamplona, Spain.
  • Maria Hernandez
    Department of Radiation Oncology, Hospital Universitario Puerta de Hierro Majadahonda, Madrid, Spain.
  • Alfredo García-Layana
    Retinal Pathologies and New Therapies Group, Experimental Ophthalmology Laboratory, Department of Ophthalmology, Clinica Universidad de Navarra, Pamplona, Spain.
  • Idoia Ochoa
    Department of Electrical and Electronics Engineering, School of Engineering (Tecnun), University of Navarra, Pamplona, Spain.
  • Sergio Recalde
    Retinal Pathologies and New Therapies Group, Experimental Ophthalmology Laboratory, Department of Ophthalmology, Clinica Universidad de Navarra, Pamplona, Spain.