Residual Network-Based Deep Learning Framework for Diabetic Retinopathy Detection

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Publicado en:Journal of Database Management vol. 36, no. 1 (2025), p. 1-22
Autor principal: Bhardwaj, Akashdeep
Otros Autores: Kumar, Manoj, Kaushik, Keshav, Cheng, Xiaochun, Dahiya, Susheela, Shankar, Achyut, Mehrotra, Tushar
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IGI Global
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Acceso en línea:Citation/Abstract
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022 |a 1063-8016 
022 |a 1533-8010 
022 |a 1047-9430 
024 7 |a 10.4018/JDM.368006  |2 doi 
035 |a 3159692893 
045 2 |b d20250101  |b d20250331 
084 |a 11186  |2 nlm 
100 1 |a Bhardwaj, Akashdeep  |u University of Petroleum and Energy Studies, India 
245 1 |a Residual Network-Based Deep Learning Framework for Diabetic Retinopathy Detection 
260 |b IGI Global  |c 2025 
513 |a Journal Article 
520 3 |a Artificial intelligence and machine learning have been transforming the health care industry in many areas such as disease diagnosis with medical imaging, surgical robots, and maximizing hospital efficiency. The Healthcare service market utilizing Artificial Intelligence is expected to reach 45.2 billion U. S. Dollars by 2026 from its current valuation, off $4.9 billion. Diabetic Retinopathy (DR) is a disease that results from complications of type one and Type two diabetes and affects patients' eyes. Diabetic retinopathy, if remains unaddressed, is one of the most serious complications of diabetes, resulting in permanent blindness. The disease has been affecting the lives of 347 million people worldwide. The paper aims to propose a residual network-based deep learning framework for the detection of diabetic retinopathy. The accuracy of our approach is 83% whereas the precision value for checking the absence of DR is 95%. 
653 |a Tomography 
653 |a Diabetes 
653 |a Accuracy 
653 |a Datasets 
653 |a Deep learning 
653 |a Blood vessels 
653 |a Health services 
653 |a Medical diagnosis 
653 |a Diabetic retinopathy 
653 |a Machine learning 
653 |a Medical personnel 
653 |a Medical imaging 
653 |a Blindness 
653 |a Efficiency 
653 |a Disease 
653 |a Health care industry 
653 |a Artificial intelligence 
653 |a Valuation 
653 |a Retinopathy 
653 |a Robotics 
653 |a Robots 
653 |a Neural networks 
653 |a Support vector machines 
653 |a Classification 
653 |a Databases 
653 |a Patients 
653 |a Algorithms 
700 1 |a Kumar, Manoj  |u University of Wollongong in Dubai, UAE 
700 1 |a Kaushik, Keshav  |u ASET, Amity University Punjab, Mohali, India 
700 1 |a Cheng, Xiaochun  |u Middlesex University, UK 
700 1 |a Dahiya, Susheela  |u Graphic Era Hill University, India 
700 1 |a Shankar, Achyut  |u Bennett University, Greater Noida, India 
700 1 |a Mehrotra, Tushar  |u Galgotias University, Greater Noida, India 
773 0 |t Journal of Database Management  |g vol. 36, no. 1 (2025), p. 1-22 
786 0 |d ProQuest  |t ABI/INFORM Global 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3159692893/abstract/embedded/75I98GEZK8WCJMPQ?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3159692893/fulltextPDF/embedded/75I98GEZK8WCJMPQ?source=fedsrch