Applications of generative adversarial networks in the diagnosis, prognosis, and treatment of ophthalmic diseases.

ABSTRACT:

Purpose

Generative adversarial networks (GANs) are key components of many artificial intelligence (AI) systems that are applied to image-informed bioengineering and medicine. GANs combat key limitations facing deep learning models: small, unbalanced datasets containing few images of severe disease. The predictive capacity of conditional GANs may also be extremely useful in managing disease on an individual basis. This narrative review focusses on the application of GANs in ophthalmology, in order to provide a critical account of the current state and ongoing challenges for healthcare professionals and allied scientists who are interested in this rapidly evolving field.

Methods

We performed a search of studies that apply generative adversarial networks (GANs) in diagnosis, th

SUBMITTER: Doorly R 

PROVIDER: S-EPMC12414077 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature