Paper Title
DIABETES DIAGNOSIS REVOLUTIONIZED PREDICTIVE POWER OF CONVOLUTIONAL NEURAL NETWORK (CNN)
Article Identifiers
Authors
Thadeus Cruz Govindapillai , Abishek A
Keywords
CNN, Diabetes, Healthcare, Prediction, Data
Abstract
Diabetes mellitus is a major global health concern. It is a chronic metabolic illness marked by increased blood sugar levels. Effective diabetes management and the reduction of related complications depend on early detection and action. Convolutional Neural Networks (CNNs), in particular, are machine learning algorithms that have demonstrated potential in predictive modeling for healthcare applications in recent years. In this work, a thorough review of the use of CNNs for diabetes risk prediction using medical imaging data—such as retinal images—is presented. We go over the design of CNNs, the reasoning behind using them, and how these models are trained and assessed. We also discuss future avenues for research and clinical use, as well as possible advantages and disadvantages of CNN-based diabetic prediction. The utilization of CNNs for diabetes prediction presents significant opportunities to enhance patient outcomes in the management of diabetes by promoting early intervention, increasing diagnostic accuracy, and facilitating treatment.
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How To Cite
"DIABETES DIAGNOSIS REVOLUTIONIZED PREDICTIVE POWER OF CONVOLUTIONAL NEURAL NETWORK (CNN)", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 3, page no.d287-d290, March-2024, Available :https://ijnrd.org/papers/IJNRD2403339.pdf
Issue
Volume 9 Issue 3, March-2024
Pages : d287-d290
Other Publication Details
Paper Reg. ID: IJNRD_215941
Published Paper Id: IJNRD2403339
Downloads: 000121137
Research Area: Engineering
Country: Coimbatore, Tamil Nadu, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2403339.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2403339
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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
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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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition


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