Paper Title
Diagnosis of Diabetic Retinopathy Using Deep Neural Network
Article Identifiers
: Authors
Keywords
Retinopathy in Diabetes, Fundus representation, Convolutional Neural Architecture, Image categorization.
Abstract
Diabetic retinopathy (DR) is a leading cause of blindness in working-age adults and requires early diagnosis and intervention to prevent vision loss. In this study, we present automatic diagnosis using deep learning techniques, especially efficient network architecture, to classify retinal images into different stages of DR. It is a system that facilitates timely treatment and management of patients by increasing the efficiency and accuracy of DR diagnosis. The experimental results demonstrate the effectiveness of the proposed method in accurately identifying DR stages and have high potential for implementation in clinical practice. This study discusses the basics of diabetes, its prevalence, problems, and wisdom on early detection and classification of diabetic retinopathy. This study also discusses AI-based technologies such as machine learning and deep learning. New research areas such as adaptive learning, interdisciplinary learning, and artificial intelligence are also being explored using various communication methods to explain diabetic retinopathy. Current literature, screening, efficacy evaluations, biomarkers of diabetic retinopathy, possible complications and list of ophthalmic complications, and future implications are discussed. There is no other information available from the authors to describe the current status of the PRISMA approach and the experience on which it is based.
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How To Cite (APA)
Adarsh Patel, Aashutosh Kumar, Vikash Kumar , & Ajay Kumar (April-2024). Diagnosis of Diabetic Retinopathy Using Deep Neural Network . INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), e349-e353. https://ijnrd.org/papers/IJNRD2404439.pdf
Issue
Volume 9 Issue 4, April-2024
Pages : e349-e353
Other Publication Details
Paper Reg. ID: IJNRD_217557
Published Paper Id: IJNRD2404439
Downloads: 000122254
Research Area: Engineering
Author Type: Indian Author
Country: Meerut, Uttar Pradesh, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2404439.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404439
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