Diabetic Retinopathy Detection, or RetinaCare, is an AI-driven solution aimed at identifying diabetic retinopathy, a critical complication of diabetes, using retinal images. Our project offers a ...

Diabetic retinopathy (DR) is a leading cause of vision loss among individuals with diabetes. Early detection and timely treatment of DR are crucial to prevent irreversible damage. In recent years, ...

Deep learning (DL) allows for the creation of computer models that have many processing layers and are capable of learning data representations at different levels of abstraction. DL algorithms have ...

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 ...

Lead researcher Lily Peng, M.D., Ph.D., of Google Inc., Mountain View, Calif., and colleagues applied deep learning to create an algorithm for automated detection of diabetic retinopathy and ...

Diabetic retinopathy (DR), a leading cause of vision impairment worldwide, primarily impacts individuals with diabetes, making early detection vital to prevent irreversible vision loss. Leveraging ...

Keywords: meta analysis, deep learning, diabetic retinopathy, image detection, optical coherence tomography. Citation: Bi Z, Li J, Liu Q and Fang Z (2025) Deep learning-based optical coherence ...

This project focuses on detecting the stages of Diabetic Retinopathy using deep learning models and comparing the performance of two powerful algorithms: EfficientNetB3 and EfficientNetB4. Abstract ...