Deep learning-based methods have become the dominant methodology in medical image
processing with the advancement of deep learning in natural image classification, detection …

Diabetic retinopathy diagnostic assessment and treatment options have improved
dramatically since the 2002 American Diabetes Association Position Statement (1). These …

Purpose To review the current therapeutic options for the management of diabetic
retinopathy (DR) and diabetic macular edema (DME) and examine the evidence for …

Diabetic macular edema (DME) is the most common cause of vision loss in patients with
diabetic retinopathy with an increasing prevalence tied to the global epidemic in type 2 …

Computer-aided diagnosis (CAD) of retinal pathologies is a current active area in medical
image analysis. Due to the increasing use of retinal optical coherence tomography (OCT) …

Importance Anti–vascular endothelial growth factor (VEGF) medicines have revolutionized
diabetic macular edema (DME) treatment. A recent randomized clinical trial comparing anti …

Objectives/Hypothesis Disease‐specific reductions in patient productivity can lead to
substantial economic losses to society. The purpose of this study was to: 1) define the …

Due to the increasing prevalence of diabetes mellitus, demand for diabetic retinopathy (DR)
screening platforms is steeply increasing. Early detection and treatment of DR are key public …

Background Diabetic retinopathy (DR) is a blinding yet treatable complication of diabetes.
DR screening is highly cost-effective at reducing blindness. Amidst the rapidly growing …

Purpose: To develop a deep learning (DL) model to detect morphologic patterns of diabetic
macular edema (DME) based on optical coherence tomography (OCT) images. Methods: In …