An Enhanced Convolutional Neural Network (CNN)-based P-EDR Mechanism for Diagnosis of Diabetic Retinopathy (DR) using Machine Learning" was published in the journal Engineering, Technology & Applied Science Research.

The article "An Enhanced Convolutional Neural Network (CNN)-based P-EDR Mechanism for Diagnosis of Diabetic Retinopathy (DR) using Machine Learning" presents a novel method for diagnosing diabetic retinopathy (DR), a leading cause of blindness, using advanced machine learning techniques. The proposed approach leverages an enhanced Convolutional Neural Network (CNN), specifically designed to improve the accuracy of DR detection through the P-EDR mechanism (presumably a feature extraction or enhancement process related to the CNN model). By integrating deep learning with medical imaging data, the mechanism aims to provide more reliable and efficient diagnosis, helping to detect DR at early stages. The study demonstrates how CNN-based models can be optimized for medical applications, potentially leading to better patient outcomes and support for healthcare professionals.