Early Detection of Diabetic Retinopathy Using ResNet-18

Rohan Doggalli, Aakash Deep, Rohith Naik V, Vinay B Achari, Vijaykumar Muttagi, Uday Kulkarni

2025

Abstract

Diabetic retinopathy (DR) is a leading cause of preventable blindness, especially among diabetic patients. Early diagnosis is critical to halt its progression and prevent vision loss. This work leverages deep learning, specifically the ResNet-18 model, to detect DR from retinal images. Using a Kaggle dataset divided into training and validation sets, the model achieved a training accuracy of 98.57% and a validation ac- curacy of 83.49%. These findings underscore the efficacy of ResNet-18 in automating DR detection. Integrating such technology into clinical workflows has the potential to enhance early screening and treatment strategies, improving patient outcomes while optimizing healthcare re- sources.

Paper Citation

in Harvard Style

Doggalli R., Deep A., Naik V R., B Achari V., Muttagi V. and Kulkarni U. (2025). Early Detection of Diabetic Retinopathy Using ResNet-18. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 3: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 81-90. DOI: 10.5220/0013609200004664

in Bibtex Style

@conference{incoft25,
author={Rohan Doggalli and Aakash Deep and Rohith Naik V and Vinay B Achari and Vijaykumar Muttagi and Uday Kulkarni},
title={Early Detection of Diabetic Retinopathy Using ResNet-18},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 3: INCOFT},
year={2025},
pages={81-90},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013609200004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 3: INCOFT
TI - Early Detection of Diabetic Retinopathy Using ResNet-18
SN - 978-989-758-763-4
AU - Doggalli R.
AU - Deep A.
AU - Naik V R.
AU - B Achari V.
AU - Muttagi V.
AU - Kulkarni U.
PY - 2025
SP - 81
EP - 90
DO - 10.5220/0013609200004664
PB - SciTePress