Abstract
Artificial intelligence (AI) is currently one of the hottest topics in ophthalmic research. AI has been used with great success for an
assortment of imaging-based tasks, such as screening, diagnosis, and staging of ophthalmic diseases. There are, however, other
useful ways of employing AI. Instead of simply classifying an image, the so-called generative AI algorithms are able to do the
reverse—generate new images based on input. With this approach, it is possible, for example, to predict retinal appearance after
treatment, enhance images, and convert between imaging modalities. This article aims to summarize the most promising of such generative AI algorithms in ophthalmology.
assortment of imaging-based tasks, such as screening, diagnosis, and staging of ophthalmic diseases. There are, however, other
useful ways of employing AI. Instead of simply classifying an image, the so-called generative AI algorithms are able to do the
reverse—generate new images based on input. With this approach, it is possible, for example, to predict retinal appearance after
treatment, enhance images, and convert between imaging modalities. This article aims to summarize the most promising of such generative AI algorithms in ophthalmology.
| Original language | English |
|---|---|
| Journal | Oftalmolog |
| Pages (from-to) | 27-30 |
| Number of pages | 4 |
| ISSN | 0108-5344 |
| Publication status | Published - 2023 |