Ophthalmology Optical Coherence Tomography Databases for Artificial Intelligence Algorithm: A Review.
David RestrepoJustin Michael QuionFrederico Do Carmo NovaesIago Diogenes Azevedo CostaConstanza VasquezAlyssa Nicole BautistaEllaine QuiminianoPatricia Abigail LimRoger MwavuLeo Anthony CeliLuis Filipe NakayamaPublished in: Seminars in ophthalmology (2024)
Current publicly available OCT databases for AI applications exhibit limitations, stemming from their non-representative nature and the lack of comprehensive demographic information. Limited datasets hamper research and equitable AI development. To promote equitable AI algorithmic development in ophthalmology, there is a need for the creation and dissemination of more representative datasets.