• P. Praveena
• Dr. S. Naganandinisujatha

Damaged blood vessels in the retina, a light-sensitive tissue located at the back of the eye, cause diabetic retinopathy, an ophthalmological disorder that damages the eyes. The blood must keep entering the eye's retina. The tiny blood arteries provide the retina with blood. High blood sugar levels might cause damage to the retinal blood vessels. Weak, readily bleeding blood vessels that were formed from scar tissue on damaged blood vessels are the cause of diabetic retinopathy. Diabetic Retinopathy (DR) may initially result in mild visual impairments or no symptoms at all. If diabetic retinopathy patients wait longer, they will lose their vision. Vision loss can be prevented by identifying and treating the problem early. Proliferative and non-proliferative are the two primary stages of this sickness that an ophthalmologist can identify. Non-proliferative diabetes comes in three stages: mild, moderate, and severe. Because diabetic retinopathy is asymptomatic, it necessitates thorough and systematic examination of the retina. Optimized DR stage grading is provided by Deep Learning models employing retinal fundus images, which aids ophthalmologists in their work. Deep learning techniques, datasets, evaluation metrics, and DR detection and grading systems are all covered in this overview.

Diabetic Retinopathy, Deep Learning, Classification.

"An overview of deep learning techniques, datasets, architectures, and assessment metrics for automated diabetic retinopathy detection and grading systems", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.d526-d534, May-2025, Available :http://www.jetir.org/papers/JETIR2505403.pdf

"An overview of deep learning techniques, datasets, architectures, and assessment metrics for automated diabetic retinopathy detection and grading systems", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. ppd526-d534, May-2025, Available at : http://www.jetir.org/papers/JETIR2505403.pdf