Findings from King Saud University Provide New Insights into Diabetic Retinopathy (Esoa-hgru: Egret Swarm Optimization Algorithm-based Hybrid Gated Recurrent Unit for Classification of Diabetic Retinopathy).

Researchers from King Saud University in Riyadh, Saudi Arabia have developed a new approach to classify diabetic retinopathy, a retinal eye disease that can lead to blindness. The proposed technique utilizes a hybrid model that combines a Mask Region-Based Convolutional Neural Network with a Bidirectional Gated Recurrent Unit. The model was optimized using the Egret Swarm Optimization algorithm and achieved high precision, recall, and F-measure scores. The study used three large datasets to validate the effectiveness of the approach. This research provides valuable insights into the diagnosis and classification of diabetic retinopathy using machine learning algorithms. [Extracted from the article]