Purpose Age‐related macular degeneration (AMD) is a complex eye disorder affecting
millions worldwide. This article uses deep learning techniques to investigate the relationship …

Purpose: Deep convolutional neural networks (CNNs) are increasingly being used for eye
disease screening and diagnosis. Especially the best performing variants, however, are …

Background The ability of deep learning (DL) algorithms to identify eyes with neovascular
age-related macular degeneration (nAMD) from optical coherence tomography (OCT) scans …

Both genetic and environmental factors influence the etiology of age-related macular
degeneration (AMD), a leading cause of blindness. AMD severity is primarily measured by …

Purpose: Because age-related macular degeneration (AMD) is a progressive disorder and
advanced AMD is currently hard to cure, an accurate and informative prediction of a person's …

Late-stage age-related macular degeneration (AMD) is a common sight-threatening disease
of the central retina affecting approximately 1 in 30 Caucasians. Besides age and smoking …

Age-related macular degeneration (AMD) is a leading cause of blindness in the developed
world. In this study, we compare the performance of retinal fundus images and genetic …

Purpose Current prediction models for advanced age-related macular degeneration (AMD)
are based on a restrictive set of risk factors. The objective of this study was to develop a …

Age-related macular degeneration (AMD) is a common retina degenerative disease with a
complex genetic and environmental background. This study aimed to determine the …

Neovascular age-related macular degeneration (nAMD) is among the main causes of visual
impairment worldwide. We built a deep learning model to distinguish the subtypes of nAMD …