Eye Disease Detection Using CNN, ResNet, and VGG16

This chapter deals with the application of deep learning models, specifically convolutional neural networks (CNNs), ResNet, VGG16, and VGG19, in the domain of eye disease detection. Early and accurate diagnosis of eye conditions is critical for preserving vision and preventing irreversible damage. Our research involves collecting and preprocessing ophthalmic images, customizing and training deep learning models, and rigorously evaluating their performance across a diverse dataset. We also provide a practical case study demonstrating the real-world application of these AI models in clinical contexts, showcasing their potential to expedite diagnosis and support healthcare professionals. The report concludes with insights into future research directions, recognizing the evolving landscape of AI in healthcare and its promising role in improving eye disease detection.