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A Review on Early Detection and Progression Prediction of Diabetic Retinopathy using Multimodal Analysis

by Swati Kiran Rajput, Prachi Karale
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 187 - Number 102
Year of Publication: 2026
Authors: Swati Kiran Rajput, Prachi Karale
10.5120/ijca60d389c72543

Swati Kiran Rajput, Prachi Karale . A Review on Early Detection and Progression Prediction of Diabetic Retinopathy using Multimodal Analysis. International Journal of Computer Applications. 187, 102 ( May 2026), 22-27. DOI=10.5120/ijca60d389c72543

@article{ 10.5120/ijca60d389c72543,
author = { Swati Kiran Rajput, Prachi Karale },
title = { A Review on Early Detection and Progression Prediction of Diabetic Retinopathy using Multimodal Analysis },
journal = { International Journal of Computer Applications },
issue_date = { May 2026 },
volume = { 187 },
number = { 102 },
month = { May },
year = { 2026 },
issn = { 0975-8887 },
pages = { 22-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume187/number102/a-review-on-early-detection-and-progression-prediction-of-diabetic-retinopathy-using-multimodal-analysis/ },
doi = { 10.5120/ijca60d389c72543 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2026-05-17T02:29:05.472820+05:30
%A Swati Kiran Rajput
%A Prachi Karale
%T A Review on Early Detection and Progression Prediction of Diabetic Retinopathy using Multimodal Analysis
%J International Journal of Computer Applications
%@ 0975-8887
%V 187
%N 102
%P 22-27
%D 2026
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Diabetic Retinopathy (DR), a major complication of diabetes mellitus, is a leading cause of vision impairment and blindness in the working-age population globally. The intricate nature of DR, characterized by gradual retinal damage due to prolonged high blood sugar levels, makes its early detection and management critical. However, the current landscape of DR diagnosis and management faces significant challenges, primarily stemming from the limitations in existing diagnostic methods and the lack of comprehensive patient data integration. This work addresses these challenges by proposing a novel approach that leverages multimodal data fusion, utilizing machine learning (ML), deep learning (DL), and artificial intelligence (AI) techniques, aiming to enhance the accuracy, pre-emption, and clinical management of DR.

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Index Terms

Computer Science
Information Sciences

Keywords

Diabetic Retinopathy Deep Learning Fundus images OCT scans

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