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  Published Paper Details:

  Paper Title

Prediction of Diabetic Retinopathy through Retinal Images using Deep Learning

  Authors

  Yogesh Kumar P G,  Bhuvaneswari M,  Singarachelvan S,  Sriram V,  Suganthan N

  Keywords

DR grading, DR detection, Deep learning, Convolutional neural network, Retinal fundus images.

  Abstract


Diabetic retinopathy (DR) is a significant cause of vision impairment among individuals with diabetes. Early detection and timely intervention are crucial for preventing vision loss. This study presents a deep learning-based approach for the prediction of diabetic retinopathy using retinal images. We employed a convolutional neural network (CNN) architecture to extract meaningful features from a large dataset of retinal images. The dataset consisted of both normal and diabetic retinopathy-affected images, with gradings for the severity of DR. Our model achieved promising results in classifying retinal images into different stages of diabetic retinopathy, with high accuracy and sensitivity.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2403224

  Paper ID - 252288

  Page Number(s) - b790-b798

  Pubished in - Volume 12 | Issue 3 | March 2024

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Yogesh Kumar P G,  Bhuvaneswari M,  Singarachelvan S,  Sriram V,  Suganthan N,   "Prediction of Diabetic Retinopathy through Retinal Images using Deep Learning", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 3, pp.b790-b798, March 2024, Available at :http://www.ijcrt.org/papers/IJCRT2403224.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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