The health care sector is totally different from any other industry. It is a high priority sector
and consumers expect the highest level of care and services regardless of cost. The health …

Background Effective screening is a desirable method for the early detection and successful
treatment for diabetic retinopathy, and fundus photography is currently the dominant medium …

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 …

We propose an automatic diabetic retinopathy (DR) analysis algorithm based on two-stages
deep convolutional neural networks (DCNN). Compared to existing DCNN-based DR …

Convolutional Neural Networks (CNNs) have gained remarkable success in computer
vision, which is mostly owe to their ability that enables learning rich image representations …

Diabetic retinopathy is when damage occurs to the retina due to diabetes, which affects up
to 80 percent of all patients who have had diabetes for 10 years or more. The expertise and …

Diabetes is a widespread disease in the world and can lead to diabetic retinopathy, macular
edema, and other obvious microvascular complications in the retina of the human eye. This …

We proposed a deep learning method for interpretable diabetic retinopathy (DR) detection.
The visual-interpretable feature of the proposed method is achieved by adding the …

Diabetic retinopathy (DR) is a common retinal disease that leads to blindness. For diagnosis
purposes, DR image grading aims to provide automatic DR grade classification, which is not …

Digital retinal imaging is a challenging screening method for which effective, robust and cost-
effective approaches are still to be developed. Regular screening for diabetic retinopathy …