A Review of Deep Learning‑Based Classification of Diabetic Retinopathy
DOI:
https://doi.org/10.66069/ojspub.26820708Keywords:
Diabetic retinopathy, Deep learning, Convolutional neural networks, Image classification, Computer‑aided diagnosisAbstract
Diabetic retinopathy (DR) is a leading cause of blindness in diabetic patients, and early accurate classification is critical for disease management. Leveraging automated feature extraction, deep learning has become a core tool for DR classification. This review outlines commonly used datasets and evaluation metrics, then systematically surveys the application of classical deep learning models—particularly convolutional neural networks—in DR severity grading, comparing their performance and discussing current challenges and future directions.
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