AI-Powered Diagnostic Tool for Retinal Disease Detection Using Convolutional Neural Networks

Accurate and timely detection of retinal disease helps prevent severe vision impairment, although traditional diagnostics take plenty of time and are demanding to perform. This led to the design of the advanced diagnostic tool, in which AI and Convolutional Neural Networks (CNNs) will enhance the identification of retinal disorders. This system will analyze a retina image to detect among others, diabetic retinopathy and age-related macular degeneration, among others. Advanced deep learning algorithms enable the tool to rapidly identify the subtle patterns and anomalies in retinal scans, which even an astute human analyst might not identify, providing insightful and diagnostic support to healthcare experts. This AI-based approach leads to the acceleration of the diagnostic workflow and the minimization of errors, which elevates overall diagnostic accuracy and allows earlier intervention. This technology will contribute to making high-quality retinal care more accessible and efficient, finally arriving at the benefit of a patient at an earlier time of early detection and treatment.

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Publication Details

Published
2024-11-18
DOI
https://doi.org/10.1109/icdici62993.2024.10810959
Citations
2
Primary Topic
Retinal Imaging and Analysis
Type
article
Field-Weighted Citation Impact
0.81
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article

AI-Powered Diagnostic Tool for Retinal Disease Detection Using Convolutional Neural Networks

Kartik Kumar, Manikandan Moovendran, J. M. Sashanth
2 citations
Retinal Imaging and Analysis
0.81
article

AI-Powered Diagnostic Tool for Retinal Disease Detection Using Convolutional Neural Networks

Kartik Kumar, Manikandan Moovendran, J. M. Sashanth
article en
2 citations

Abstract

Accurate and timely detection of retinal disease helps prevent severe vision impairment, although traditional diagnostics take plenty of time and are demanding to perform. This led to the design of the advanced diagnostic tool, in which AI and Convolutional Neural Networks (CNNs) will enhance the identification of retinal disorders. This system will analyze a retina image to detect among others, diabetic retinopathy and age-related macular degeneration, among others. Advanced deep learning algorithms enable the tool to rapidly identify the subtle patterns and anomalies in retinal scans, which even an astute human analyst might not identify, providing insightful and diagnostic support to healthcare experts. This AI-based approach leads to the acceleration of the diagnostic workflow and the minimization of errors, which elevates overall diagnostic accuracy and allows earlier intervention. This technology will contribute to making high-quality retinal care more accessible and efficient, finally arriving at the benefit of a patient at an earlier time of early detection and treatment.

SRM Institute of Science and Technology (IN)
Openalex Percentile: Top 24%
Retinal Imaging and Analysis
0.81
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