Eye Disease Detection Using Deep Learning

The escalating global challenge of diagnosing and managing eye diseases such as cataracts, diabetic retinopathy, and glaucoma three of the leading causes of visual impairment and blindness.The project leverages recent advances in artificial intelligence, particularly deep learning and transfer learning using convolutional neural networks (CNNs), to develop an automated diagnostic system for identifying these diseases from retinal images.Utilizing publicly available datasets, the system is trained via models like VGG19 and is ultimately deployed through a user-friendly web application using Flask.The goal is to enhance early detection, support clinicians, and make screening accessible in underserved regions, thereby reducing preventable blindness and improving healthcare equity.