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Enhancing Early Detection of Diabetic Retinopathy Through Deep Learning and XAI

Eyes reveal disease—
Deep learning spots early signs,
Vision preserved well.
Deep learning
Diabetic retinopathy
Medical imaging
XAI
Healthcare

K. A. Alavee, M. H. Zillanee, M. Mostakim, M. A. Samad, et al., “Enhancing Early Detection of Diabetic Retinopathy Through Deep Learning and XAI,” IEEE Access (2024), doi: 10.1109/access.2024.3405570

Authors

K. A. Alavee

M. H. Zillanee

M. Mostakim

Md Abdus Samad

Published

June 2024

Doi

10.1109/access.2024.3405570

Abstract

Diabetic retinopathy is a leading cause of blindness among diabetic patients, making early detection crucial for preventing vision loss. This study proposes a deep learning framework enhanced with explainable AI (XAI) techniques for early detection of diabetic retinopathy from retinal fundus images. The integration of XAI provides interpretable predictions, enabling clinicians to understand model decisions and trust automated screening systems.

Citation

 Add to Zotero 

@article{AlaveeEtAl:2024,
  Author  = {Alavee, K. A. and Zillanee, M. H. and Mostakim, M. and Samad, M. A. and others},
  Title   = {Enhancing Early Detection of Diabetic Retinopathy Through Deep Learning and XAI},
  Journal = {IEEE Access},
  Year    = {2024},
  Doi     = {10.1109/access.2024.3405570}
}