Year: 2025
Type: article
Abstract: : ❖The DeepDiabetic project revolutionizes the diagnosis of diabetic eye diseases, particularly diabetic retinopathy, by leveraging deep learning to automate and enhance the accuracy of retinal image analysis. Unlike traditional manual methods, which are slow and error-prone, DeepDiabetic employs the VGG-16 convolutional neural network to efficiently classify disease severity and detect related conditions. Advanced techniques, such as attention mechanisms and GAN-based data augmentation, improve feature extraction and address data limitations. Offering superior accuracy and a user-friendly interface, it streamlines clinical workflows and holds potential for broader application to other retinal disorders, advancing ophthalmic healthcare.
DOI: 10.55041/ijsrem48139
Author: Mr. CHANDRU.S
Language: English
Topic: Retinal Imaging and Analysis
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W4410508362