General Deep Learning Model for Detecting Diabetic Retinopathy

Diabetic retinopathy (DR) is a common and potentially sight-threatening complication of diabetes. Early detection accurate diagnosis DR are crucial for effective treatment prevention vision loss. In recent years, deep learning techniques have shown remarkable success in various medical imaging tasks. This research paper presents general model designed specifically detecting diabetic retinal images. The proposed leverages convolutional neural networks (CNNs) to automatically extract relevant features from images classify them into different stages severity. Experimental results demonstrate the effectiveness robustness accurately DR, showcasing its potential clinical deployment.