Transformative Applications of Artificial Intelligence in Ophthalmology: A Review on Eye Disease Detection

Artificial Intelligence has emerged as a promising tool within ophthalmology for accurate and fast detection of a wide range of eye diseases. We provide a critical review here of some of the transformative applications of AI in the field of ophthalmology with a simple CNN model for the detection of eye diseases. A simple CNN model is also presented to detect the eye diseases and the model has been trained and tested using a dataset comprising images of the retina, with preprocessing by applying techniques of data augmentation: resizing, flipping, and rotation. Results demonstrate the potential of AI and, more important, CNN models to enhance the accuracy and speed of eye disease diagnosis, reduce the workload of ophthalmologists, and improve patient outcomes. This study also discussed challenges and limitations of AI in ophthalmology, such as the need for large and diverse datasets, the importance of interpretability and explainability, and the possible ethical and regulatory issues. This review is an asset for both researchers and practitioners in ophthalmology, showing the transformative value of AI with the promise that CNN models have in detecting eye diseases.