The advent of deep learning in ophthalmology has revolutionised the detection and diagnosis of diabetic retinopathy (DR). By utilising convolutional neural networks (CNNs) and advanced image ...

Researchers at Edith Cowan University (ECU) have developed a cutting-edge Artificial Intelligence (AI) system that could ...

Automated machine-learning models accurately identified risk for diabetic retinopathy progression using ultra-widefield retinal images, according to a study published in JAMA Ophthalmology ...

A report from Media.Market.us said that the Global AI-Powered Retina Image Analysis Market Size is projected to expand significantly, reaching approximately US$ 9.4 billion by 2033, up from US$ 2. ...

An artificial intelligence (AI) model integrated into a retina tracker for diabetic retinopathy can achieve high accuracy while being resource-efficient, according to a study presented at ENDO 2025, ...

A team from New York conducted a study that showed how diabetic retinopathy risk can be determined by fundus photography. By training AI on a machine learning algorithm, the images can be assessed ...

Specifically, when the model was trained using images from all seven fields, the area under the curve (AUC) was 0.68 at 6 months and 0.77 at 24 months. When the researchers restricted training to ...

Diabetic retinopathy detection and treatment can reduce the risk of blindness by 95%; however, half of Americans living with diabetes do not receive their annual eye exam. Patients face barriers ...

Study: A foundation model for generalizable disease detection from retinal images. Image Credit: GeebShot / Shutterstock.com About the study RETFound is a SSL model that was trained on 1.6 million ...