Jun 20 – 22, 2026
India International Centre, New Delhi
Asia/Kolkata timezone

Machine Learning-Based Early Detection of Diabetic Retinopathy Using Fundus Imaging: A Multi-Center Validation Study

Not scheduled
20m
India International Centre, New Delhi

India International Centre, New Delhi

Speaker

Priya Sharma (All India Institute of Medical Sciences (AIIMS), New Delhi)

Description

Background: Diabetic retinopathy affects approximately 103 million people worldwide. Early detection is critical, yet many healthcare systems lack sufficient ophthalmologists.

Objective: To develop and validate a deep learning model for automated detection of referable DR from fundus photographs.

Methods: Trained EfficientNet-B4 on 128,457 images, validated on 15,832 from three independent centers in India, Nigeria, and Brazil.

Results: AUC-ROC 0.967 (95% CI: 0.961-0.973). Sensitivity 94.2%, specificity 91.8%. Consistent across ethnic groups (p=0.34). Inference time 0.8s per image.

Conclusion: AI-assisted DR screening achieves near-expert performance across diverse populations.

Author

Priya Sharma (All India Institute of Medical Sciences (AIIMS), New Delhi)

Presentation materials

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