An overview of the applications of deep learning for ophthalmic diagnosis using retinal
fundus images is presented. We describe various retinal image datasets that can be used for …

Progress in artificial intelligence and tele-ophthalmology for diabetic retinopathy screening,
including artificial intelligence applications in 'real-world settings' and cost-effectiveness …

Background Age-related macular degeneration (AMD) is one of the leading causes of vision
loss in the elderly population. The application of artificial intelligence (AI) provides …

Purpose: To build and validate artificial intelligence (AI)-based models for AMD screening
and for predicting late dry and wet AMD progression within 1 and 2 years. Methods: The …

Regulatory approval of the first two therapeutic substances for the management of
geographic atrophy (GA) secondary to age-related macular degeneration (AMD) is a major …

W ith aging populations, health systems worldwide are struggling to provide adequate eye
care at the population level, giving rise to projections of increasing levels of visual …

Glaucoma, diabetic retinopathy, diabetic hypertension (DHR), Cataract, and age-related
macular degeneration are some of the most common and important retinal diseases. A …

Background Applications for artificial intelligence (AI) in ophthalmology are continually
evolving. Fundoscopy is one of the oldest ocular imaging techniques but remains a mainstay …

Background and Objective. Glaucomatous vision loss may be preceded by an enlargement
of the cup‐to‐disc ratio (CDR). We propose to develop and validate an artificial‐intelligence …

In recent years, the use of machine learning and artificial intelligence for the diagnosis and
monitor of various ocular disorders has been increasing remarkably. It has emerged as an …