In clinical ophthalmology, a variety of image-related diagnostic techniques have begun to
offer unprecedented insights into eye diseases based on morphological datasets with …

Use of artificial intelligence in medicine in an evolving technology which holds promise for
mass screening and perhaps may even help in establishing an accurate diagnosis. The …

Objectives To assess the role of artificial intelligence (AI)-based automated software for
detection of diabetic retinopathy (DR) and sight-threatening DR (STDR) by fundus …

Deep learning algorithms have been used to detect diabetic retinopathy (DR) with specialist-
level accuracy. This study aims to validate one such algorithm on a large-scale clinical …

Aim To evaluate the sensitivity and specificity of “fundus on phone'(FOP) camera, a
smartphone based retinal imaging system, as a screening tool for diabetic retinopathy (DR) …

Objective The study was aimed at estimating the prevalence of type 2 diabetes mellitus and
diabetic retinopathy in a rural population of South India. Design A population-based cross …

PURPOSE: To assess the cost-effectiveness of a telemedicine diabetic retinopathy (DR)
screening program in rural Southern India that conducts 1-off screening camps (ie …

Aims: To assess the knowledge and attitude toward DM and diabetic retinopathy of the
general population in a suburban town of South India. Settings and Design: Door-to-door …

Purpose We compared smartphone fundus photography, nonmydriatic fundus photography,
and 7-field mydriatic fundus photography for their abilities to detect and grade diabetic …

Prevention of blindness due to diabetic retinopathy (DR) requires effective screening
strategies, for which eye care providers need to know the magnitude of the burden and the …