(untitled) (Journal of Advances and Scholarly Researches in Allied Education, 2023)
Deep learning methods based on image processing, illness detection, and risk assessment are becoming more successful in healthcare. This research article proposes a model for diabetic retinopathy diagnosis using FastAI, where the outputs are improved by utilizing the Fast AI library and less code. This Convolution Neural Network (CNN) model is successful in terms of image processing, and it was trained using Google Colab’s GPU system. The neural network that has been pre-programmed will assist in obtaining a fast and accurate result. This suggested approach compares pictures of diabetic retinopathy to normal retina scans. A modified algorithm with a bigger dataset may be developed in the future to identify all phases of diabetic retinopathy. This CNN is designed to help ophthalmologists diagnose patients.