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

  • Sadi Can Sonmez
  • , Mertcan Sevgi
  • , Fares Antaki
  • , Josef Huemer
  • , Pearse A Keane*
  • *Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

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.

Original languageEnglish
Article numberbjo-2024-325458
Pages (from-to)1335-1340
Number of pages6
JournalBritish Journal of Ophthalmology
Volume108
Issue number10
DOIs
Publication statusPublished - 20 Sept 2024

Fields of science

  • 302007 Ophthalmology

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