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)
Based on the rise in chronic kidney disease (CKD) incidence in recent years, a more accurate early prediction model is required to identify high-risk individuals before they develop end-stage renal failure. To date, it has been determined that diabetes mellitus6, obesity5, and female sex4 are all significant risk factors for chronic renal disease. Recently, several biomarkers connected to CKD have been identified. Treatment for renal failure and chronic kidney disease is both expensive and inefficient. Only around 5% of those with early CKD are aware of their illness, though20. Once CKD is detected, glomerular damage has typically reached over 50% and is irreversible. An accurate chronic renal illness prediction can be very helpful in this regard. This study aims to forecast renal failure. Static Vector Machine (SVM)
"KIDNEY DISEASE PREDICTION USING DIFFERENT CLASSIFICATION TECHNIQUES", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.7, Issue 12, page no.b876-b883, December-2022, Available :http://www.ijnrd.org/papers/IJNRD2212196.pdf
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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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