SLIViT algorithm detects biomarkers of progression in non-neovascular AMD

ROME — A deep learning algorithm developed at University of California, Los Angeles, showed superior performance compared with other algorithms and human graders in detecting early biomarkers of age-related macular degeneration progression.
“It is important to define and detect early biomarkers for AMD progression because we want to develop drugs targeting earlier stages of non-neovascular AMD,” Giulia Corradetti, MD, said at the FLORetina-ICOOR meeting.
SLIViT, short for Slice Integration by Vision Transformers, is a deep learning framework able to measure disease-related

Leave a Comment

Your email address will not be published. Required fields are marked *

Shopping Cart