Abstract: Diabetic retinopathy (DR) remains a critical concern in the realm of ophthalmology, demanding accurate and efficient diagnostic methodologies. This paper presents a comprehensive approach ...

Objective: To systematically review and meta-analyze the effectiveness of deep learning algorithms applied to optical coherence tomography (OCT) and retinal images for the detection of diabetic ...

Published by Elsevier Ltd. We created and validated two versions of a deep ... “diabetic retinopathy screening programs”, “automated detection of diabetic retinopathy using fundus photographs”, ...

A dependable, interpretable, and scalable DR detection method ... using convolutional neural networks (CNN) to evaluate retinal fundus pictures, recent developments in deep learning have significantly ...

The evaluation of retinal images using an algorithm based on deep machine learning can improve early detection and treatment of diabetic retinopathy, claims research. Adults with type 2 diabetes ...

In the context of diabetic retinopathy detection, AI algorithms ... of modern DR methods is given in this section. In [19], researchers have introduced a multi-classification system for grading ...