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									<h1>Detection of Diabetic Retinopathy<br />
									Using Integrated Deep Learning with Image Processing Technique</h1>
									<p>This study applies deep learning techniques to detect diabetic retinopathy (DR) using convolutional neural networks (CNNs) to analyze retinal images. We enhanced image quality through preprocessing methods like noise reduction and contrast adjustment.
									Our CNN model, trained on a diverse dataset, effectively identifies patterns of DR at various stages: mild nonproliferative, moderate nonproliferative, severe nonproliferative, and proliferative diabetic retinopathy. The integrated approach shows improved sensitivity and specificity compared to traditional methods, making it a promising, cost-effective solution for early DR detection in clinical settings, crucial for preventing vision loss in diabetic patients...</p>
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