Diabetic retinopathy classification through advanced deep learning with GANs

Key Points

• The aim is to enhance the classification of diabetic retinopathy using advanced deep learning techniques with GANs.
• Implemented an advanced deep learning model
• Utilized Generative Adversarial Networks (GANs) for data augmentation
• Classified images of diabetic retinopathy based on severity levels
• Achieved higher accuracy in classification compared to traditional methods
• Demonstrated improved performance with the use of GANs for training
• Results indicate potential for clinical application in ophthalmology