Prediction of Multiple Retinal Diseaeses Using Deep Learning Algorithm and Quantum Computing

Retinal illnesses, such as age-related macular degeneration, glaucoma, retinal detachment, and diabetic retinopathy, are the main causes of vision impairment and blindness. An early and accurate identification of these conditions is necessary for effective patient care and therapy. Convolution neural networks (CNNs) are creatively used for the diagnosis and prognosis of different retinal disorders is presented in this abstract. Quantum computing may often employ the greatest amount of entangled qubits for picture reconstruction. In this study, a huge dataset of retinal pictures representing a range of retinal disorders is collected and annotated with the names of the diseases. These images undergo extensive pre-processing in order to ensure consistency and enhance the model's ability to identify relevant characteristics. To further diversity datasets, augmentation techniques are applied.