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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 10, ISSUE 12, DECEMBER 2021

Prior Stage Kidney Disease Prediction Using AI & Supervised Machine Learning Techniques

Barot mitisha, prof. barkha bhavsar

DOI: 10.17148/IJARCCE.2021.101266

Abstract: Chronic kidney disease, also known as chronic kidney disease, is a featureless disorder of kidney function or kidney function that lasts months or years. Chronic kidney disease is usually found by screening people who are known to be at risk for kidney problems such as: Therefore, early prediction is needed to combat illness and provide good treatment. This study suggests the use of CKD machine learning techniques such as KNN, DT, NB, and SB classifiers.

Keywords: Chronic kidney, KNN, DT, NB, and SB classifiers

How to Cite:

[1] Barot mitisha, prof. barkha bhavsar, “Prior Stage Kidney Disease Prediction Using AI & Supervised Machine Learning Techniques,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2021.101266