Automated diabetic retinopathy severity grading using novel DR-ResNet + deep learning model

The proposed DR-ResNet’+ model not only reduces training time by an impressive 95% but also exhibits outstanding performance metrics, including an accuracy of 0.9898, specificity of 0.9916, precision of 0.9670, sensitivity of 0.9829, and an F1-score of 0.9748, which position the proposed model as exceptionally well-suited for real-time clinical applications.