New Data from SR University Illuminate Research in Retinal Diseases and Conditions (Enhancing medical image analysis: A fusion of fully connected neural network classifier with CNN-VIT for improved retinal disease detection).

A recent research report from SR University in Telangana, India, highlights the potential of deep learning techniques, specifically Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs), in the field of medical image analysis for detecting retinal diseases. The researchers developed a unique model called a Cascade CNN-ViT, which combines the advantages of Inception-V3, ResNet-50, and Vision Transformer architectures. The model successfully integrates local features from retinal images with global contextual information, outperforming standalone CNNs and Vision Transformers. This approach has the potential to improve the management of retinal diseases and enable early detection and timely intervention. [Extracted from the article]