Advances in machine learning for ABCA4-related retinopathy: segmentation and phenotyping.

Journal: International ophthalmology
Published Date: Jul 23, 2025

Abstract

PURPOSE: Stargardt disease, also called ABCA4-related retinopathy (ABCA4R), is the most common form of juvenile-onset macular dystrophy and yet lacks an FDA approved treatment. Substantial progress has been made through landmark studies like that of the Progression of Atrophy Secondary to Stargardt Disease (ProgStar), but tasks like image segmentation and phenotyping still pose major challenges in terms of monitoring disease progression and categorizing patient subgroups. Furthermore, these methods are subjective and laborious. Recent advancements in machine learning (ML) and deep learning show considerable promise in automating these processes.

Authors

  • Yousif J Shwetar
    Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
  • Brian P Brooks
    Ophthalmic Genetics and Visual Function Branch, National Eye Institute, NIH, Bethesda, MD, USA.
  • Brett G Jeffrey
    Ophthalmic Genetics and Visual Function Branch, National Eye Institute, National Institutes of Health, Bethesda, MD, USA.
  • Benjamin D Solomon
  • Melissa A Haendel
    Library, Oregon Health & Science University, Portland, OR 97239, USA.

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