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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 Nakayama
Published 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.
Keyphrases
  • artificial intelligence
  • big data
  • machine learning
  • deep learning
  • optical coherence tomography
  • diabetic retinopathy
  • cross sectional
  • rna seq
  • healthcare
  • optic nerve