Generative artificial intelligence in ophthalmology: current innovations, future applications and challenges.

Journal: The British journal of ophthalmology
Published Date:

Abstract

The rapid advancements in generative artificial intelligence are set to significantly influence the medical sector, particularly ophthalmology. Generative adversarial networks and diffusion models enable the creation of synthetic images, aiding the development of deep learning models tailored for specific imaging tasks. Additionally, the advent of multimodal foundational models, capable of generating images, text and videos, presents a broad spectrum of applications within ophthalmology. These range from enhancing diagnostic accuracy to improving patient education and training healthcare professionals. Despite the promising potential, this area of technology is still in its infancy, and there are several challenges to be addressed, including data bias, safety concerns and the practical implementation of these technologies in clinical settings.

Authors

  • Sadi Can Sonmez
    Department of Public Health, Ege University, Izmir, Turkey.
  • Mertcan Sevgi
    Institute of Ophthalmology, University College London, London, UK.
  • Fares Antaki
    Department of Ophthalmology, University of Montreal, Montreal, QC H3T 1J4, Canada.
  • Josef Huemer
    Moorfields Eye Hospital, London, United Kingdom.
  • Pearse A Keane
    National Institute for Health Research Biomedical Research Centre for Ophthalmology, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK.