MACHINE LEARNING TECHNIQUES FOR RETINOPATHY DETECTION IN DIABETIC PATIENTS

MACHINE LEARNING TECHNIQUES FOR RETINOPATHY DETECTION IN DIABETIC PATIENTS

If left untreated, diabetic retinopathy—a common consequence of diabetes—poses a serious danger of blindness. Conventional techniques for identifying retinopathies depend on ophthalmologists manually examining retinal pictures, a laborious process prone to human error. By using cutting-edge algorit...

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Bibliographic Details
Main Authors: Ajay Kushwaha, Ahankari Sachin Suresh, Chennoju Phanindra, Anil Kumar Sahu, Devanand Bhonsle, Yamini Chouhan
Format: Article
Language:English
Published: University of Kragujevac 2025-06-01
Series:Proceedings on Engineering Sciences
Subjects:
diabetic retinopathy
automated image analysis
convolutional neural networks (cnns)
automated detection systems
diabetic eye disease screening
automated retinopathy detection
artificial intelligence for diabetic retinopathy
data augmentation in medical imaging
artificial bee colony algorithms in retinal imaging
non-proliferative diabetic retinopathy (npdr)
proliferative diabetic retinopathy (pdr)
Online Access:https://pesjournal.net/journal/v7-n2/70.pdf
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https://pesjournal.net/journal/v7-n2/70.pdf

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