Suitability of machine learning for atrophy and fibrosis development in neovascular age-related macular degeneration.
Journal:
Acta ophthalmologica
PMID:
38131161
Abstract
PURPOSE: To assess the suitability of machine learning (ML) techniques in predicting the development of fibrosis and atrophy in patients with neovascular age-related macular degeneration (nAMD), receiving anti-VEGF treatment over a 36-month period.
Authors
Keywords
Aged
Aged, 80 and over
Angiogenesis Inhibitors
Atrophy
Female
Fibrosis
Fluorescein Angiography
Follow-Up Studies
Fundus Oculi
Humans
Intravitreal Injections
Machine Learning
Male
Ranibizumab
Retrospective Studies
Tomography, Optical Coherence
Vascular Endothelial Growth Factor A
Visual Acuity
Wet Macular Degeneration