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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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Volume 9 | Issue 5
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| Paper Title: | Diagnosis of Diabetic Retinopathy Using Deep Neural Network |
| Authors Name: | Adarsh Patel , Aashutosh Kumar , Vikash Kumar , Ajay Kumar |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_217557
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| Published Paper Id: | IJNRD2404439 |
| Published In: | Volume 9 Issue 4, April-2024 |
| DOI: | |
| 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. |
| Keywords: | Retinopathy in Diabetes, Fundus representation, Convolutional Neural Architecture, Image categorization. |
| Cite Article: | "Diagnosis of Diabetic Retinopathy Using Deep Neural Network ", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.e349-e353, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404439.pdf |
| Downloads: | 00029 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2404439 Registration ID: 217557 Published In: Volume 9 Issue 4, April-2024 DOI (Digital Object Identifier): Page No: e349-e353 Country: Meerut, Uttar Pradesh, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2404439 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2404439 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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