A deep learning model for retinal disease detection

A deep learning model for the detection of retinal diseases aims to assist in the early diagnosis of conditions such as diabetic retinopathy, age-related macular degeneration, and glaucoma. These models are trained on large datasets of retinal images, allowing them to learn patterns and anomalies that indicate disease. Using convolutional neural networks (CNNs), the model can accurately detect and classify retinal abnormalities, enabling faster and more accurate diagnosis compared to traditional methods. This can significantly improve patient outcomes by providing timely treatment and reducing the risk of vision loss.