DEEP LEARNING FOR AUTOMATIC PREDICTION OF EARLY ACTIVATION OF TREATMENT-NAIVE NONEXUDATIVE MACULAR NEOVASCULARIZATIONS IN AGE-RELATED MACULAR DEGENERATION.

Emanuele CrincoliFiammetta CataniaRiccardo SacconiNicolò RibarichSilvia FerraraMariacristina ParravanoEliana CostanzoFrancesca Amoroso

Published in: Retina (Philadelphia, Pa.) (2024)

Artificial intelligence shows high performances in identifications of nonexudative macular neovascularizations at risk for exudation within the first 2 years of follow-up, allowing better customization of follow-up timing and avoiding treatment delay. Better results are obtained with the combination of OCTA and OCT B-scan image analysis.

Keyphrases

artificial intelligence
deep learning
age related macular degeneration
optical coherence tomography
machine learning
diabetic retinopathy
big data
hiv infected
convolutional neural network
combination therapy
cataract surgery