Purpose Disease staging involves the assessment of disease severity or progression and is
used for treatment selection. In diabetic retinopathy, disease staging using a wide area is …

Purpose Diabetic retinopathy (DR) is one of the leading causes of preventable blindness
globally. Performing retinal screening examinations on all diabetic patients is an unmet …

Deep learning evolves into a new form of machine learning technology that is classified
under artificial intelligence (AI), which has substantial potential for large-scale healthcare …

Importance A deep learning system (DLS) is a machine learning technology with potential
for screening diabetic retinopathy and related eye diseases. Objective To evaluate the …

Diabetic retinopathy is a leading cause of blindness among working-age adults. Early
detection of this condition is critical for good prognosis. In this paper, we demonstrate the …

Importance There has been wide interest in using artificial intelligence (AI)–based grading of
retinal images to identify diabetic retinopathy, but such a system has never been deployed …

As one of the most common diabetic complications, diabetic retinopathy (DR) can cause
retinal damage, vision loss and even blindness. Automated DR grading technology has …

Although deep learning for Diabetic Retinopathy (DR) screening has shown great success
in achieving clinically acceptable accuracy for referable versus non-referable DR, there …

Importance Deep learning is a family of computational methods that allow an algorithm to
program itself by learning from a large set of examples that demonstrate the desired …

The global burden of diabetic retinopathy (DR) continues to worsen and DR remains a
leading cause of vision loss worldwide. Here, we describe an algorithm to predict DR …