Applications of artificial intelligence to inherited retinal diseases: A systematic review.

Journal: Survey of ophthalmology
PMID: 39566565

Abstract

Artificial intelligence(AI)-based methods have been extensively used for the detection and management of various common retinal conditions, but their targeted development for inherited retinal diseases (IRD) is still nascent. In the context of limited availability of retinal subspecialists, genetic testing and genetic counseling, there is a high need for accurate and accessible diagnostic methods. The currently available AI studies, aiming for detection, classification, and prediction of IRD, remain mainly retrospective and include relatively limited numbers of patients due to their scarcity. We summarize the latest findings and clinical implications of machine-learning algorithms in IRD, highlighting the achievements and challenges of AI to assist ophthalmologists in their clinical practice.

Authors

  • Mohamad Issa
    Department of Otolaryngology - Head and Neck Surgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania.
  • Georges Sukkarieh
    Rothschild Foundation Hospital, Paris, France. Electronic address: georgessuccarieh18@gmail.com.
  • Mathias Gallardo
    AIMI, ARTORG Center, University of Bern, Bern, Switzerland. Electronic address: Mathias.Gallardo@gmail.com.
  • Ilias Sarbout
    Rothschild Foundation Hospital, Paris, France; Sorbonne University, France. Electronic address: isarbout@for.paris.
  • Sophie Bonnin
    Ophthalmology Department, Rothschild Foundation Hospital, Paris, France.
  • Ramin Tadayoni
    Ophthalmology Department, Lariboisière Hospital, AP-HP, Paris, France; Paris Cité University, Paris, France.
  • Dan Milea
    Singapore National Eye Centre.

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