Abstract
Presentation Description :
Rare eye diseases such as inherited retinal diseases (IRDs) are challenging to diagnose genetically. IRDs are typically monogenic disorders and represent a leading cause of blindness in children and working-age adults worldwide. A growing number are now being targeted in clinical trials, with approved treatments increasingly available. However, access requires a genetic diagnosis to be established sufficiently early. Critically, the timely identification of a genetic cause remains challenging. We demonstrate that a deep-learning algorithm, Eye2Gene, trained on the largest imaging dataset of patients with IRDs currently available, can identify the genetic diagnosis for the 36 most common molecular causes (top-5 accuracy = 85.6%). This algorithm has been deployed online (https://app.eye2gene.com) and externally validated on data provided by four different clinical centers. Eye2Gene can facilitate access to diagnostic expertise, only currently available in a limited number of specialist centers globally, and thereby accelerate the genetic diagnostic odyssey.
This abstract was presented at the 2023 ARVO Annual Meeting, held in New Orleans, LA, April 23-27, 2023.