Diabetic Retinopathy Detection Using Deep Learning

Diabetic Retinopathy is a serious eye disease caused by diabetes, often leading to vision impairment or blindness if not detected early. Many people remain unaware of the damage until it becomes irreversible. This project tackles that problem by leveraging advanced Deep Learning techniques—using image processing and Machine Learning models—to analyze retinal images and detect early signs of the disease. Beyond detection, the system also classifies the severity of the condition, giving patients clearer insights into their eye health. By combining technology with healthcare, it promotes early diagnosis, timely treatment, and proactive eye care, especially in areas with limited medical access. The use of accurate and efficient deep learning models ensures dependable results, making the system a valuable tool in modern eye health management. Ultimately, it empowers individuals and healthcare providers to act early, helping to prevent avoidable vision loss and improve quality of life. Key Words: Diabetic Retinopathy, Deep Learning. ResNet, Eye Health Management, Kaggle, APTOS Dataset.