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@article{179599,
        author = {Suraj Pawar and Prof. M. M Baig and Hasina Lanjewar and Gayatri Jaiswal and Anushka Bhalerao},
        title = {Detection of Diabetic Retinopathy using Convolutional Neural Networks to prevent Vision-Threatening Diseases},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {7026-7031},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179599},
        abstract = {Diabetic retinopathy (DR), a common 
complication of diabetes, can lead to severe vision loss if 
left untreated. Early detection is crucial for timely 
intervention and improved patient outcome.The propo 
sed method leverages deep learning techniques, 
specifically CNNs, to analyze retinal fundus images for 
signs of diabetic retinopathy. The CNN model was 
trained on a large dataset of labeled retinal images and 
learned to identify subtle features associated with 
different stages of the disease. The system aims to 
classify images into multiple categories ranging from no 
retinopathy to severe cases requiring immediate 
medical attention. The key advantages of this approach 
include its potential for high accuracy, scalability, and 
ability to assist healthcare professionals in efficiently 
screening large populations. The system can be 
integrated into existing healthcare workflows, 
providing rapid and consistent results to support 
clinical decision making. Preliminary results showed 
promising performance in detecting various stages of 
diabetic retinopathy, with high sensitivity and 
specificity. Future work will focus on further improving 
the model's accuracy, expanding the dataset to include 
diverse populations, and conducting clinical validation 
studies to assess the real-world effectiveness of the 
system in preventing vision- threatening complications 
of diabetes.},
        keywords = {Diabetic Retinopathy, Convolutional  Neural Networks (CNNs) , Deep Learning , Fundus  Images , Image Preprocessing.},
        month = {May},
        }