Recent Development and Application in Deep Learning for Diabetic Retinopathy Image Classification
DOI:
https://doi.org/10.47392/IRJAEM.2024.0347Keywords:
Diabetic Retinopathy, Deep learning, Image Classification, Early detection, Medical ImagingAbstract
The Diabetic Retinopathy Poses a significant risk of vision loss if not detected early. Deep learning has made Substantial strides in classifying Diabetic Retinopathy images, enhancing screening accuracy and efficiency The paper review the current advancement and application in deep learning for Diabetic Retinopathy image classification. Convolutional Neural Network, transfer learning have demonstrated notable improvement in identifying Diabetic Retinopathy stages. This review emphasizes the importance of collaborative efforts and innovative technologies in creating robust, interpretable and clinically relevant solution for early detection and management of Diabetic Retinopathy. By harnessing these advanced techniques, health care providers can better manage the increasing burden of Diabetic Retinopathy, ultimately enhancing patient care and reducing the risk of vision Loss
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