A Two-Stage Neural Network Framework for Automated Diabetic Retinopathy Detection - Dr. G. Suresh (Utilitas Mathematica, 2025)
Diabetic Retinopathy (DR) is a serious complication of diabetes that affects the retina and can lead to vision impairment or blindness if not detected early. This condition can be diagnosed by analyzing retinal images captured using a fundus camera. With advancements in artificial intelligence, particularly in deep learning, Diabetic Neural Networks (DNNs) have emerged as a powerful tool in biomedical signal analysis. These networks not only model complex image features but also effectively classify retinal images as normal or indicative of diabetic retinopathy. The automatic and accurate detection of DR plays a crucial role in timely intervention and can significantly reduce the risk of vision loss among diabetic patients.