SmartDR+: Extensible Retinal Disease Detection Platform

Diabetic Retinopathy (DR) is one of the most preva- lent causes of preventable blindness, particularly in diabetic patients. The increasing number of diabetic cases worldwide has made early screening for retinal abnormalities more critical than ever. This paper presents SmartDR+, a scalable and extensible deep learning–based framework for automated detection of DR from high-resolution retinal fundus images. The system integrates robust preprocessing techniques, transfer learning using lightweight backbones, and interpretability through Grad- CAM heatmaps [2], [4], [5], [1], [3], [6]. SmartDR+ can operate efficiently on both cloud and edge devices [2], [4], [5], [1], [3], [6], providing cost-effective, explainable, and real-time screening. Experimental evaluations on the APTOS and EyePACS datasets demonstrate competitive accuracy and interpretability. The sys- tem provides a promising direction for AI-assisted ophthalmology and telemedicine applications in rural healthcare

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Publication Details

Journal
International Journal of Advanced Research in Science Communication and Technology
Published
2025-11-13
DOI
https://doi.org/10.48175/ijarsct-29849
Primary Topic
Retinal Imaging and Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

SmartDR+: Extensible Retinal Disease Detection Platform

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International Journal of Advanced Research in Science Communication and Technology
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SmartDR+: Extensible Retinal Disease Detection Platform

Prof. H. S. Borse, Sagar Shankar Khandagale, Prathamesh Kiran Khule, Tejas Laxman Kharche, Jayesh Bhikaji Pendharkar
article en

Abstract

Diabetic Retinopathy (DR) is one of the most preva- lent causes of preventable blindness, particularly in diabetic patients. The increasing number of diabetic cases worldwide has made early screening for retinal abnormalities more critical than ever. This paper presents SmartDR+, a scalable and extensible deep learning–based framework for automated detection of DR from high-resolution retinal fundus images. The system integrates robust preprocessing techniques, transfer learning using lightweight backbones, and interpretability through Grad- CAM heatmaps [2], [4], [5], [1], [3], [6]. SmartDR+ can operate efficiently on both cloud and edge devices [2], [4], [5], [1], [3], [6], providing cost-effective, explainable, and real-time screening. Experimental evaluations on the APTOS and EyePACS datasets demonstrate competitive accuracy and interpretability. The sys- tem provides a promising direction for AI-assisted ophthalmology and telemedicine applications in rural healthcare

International Journal of Advanced Research in Science Communication and Technology
Indian Numismatic, Historical and Cultural Research Foundation (IN)
Openalex Percentile: Top 51%
Retinal Imaging and Analysis
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