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ISSN 1004-9037
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Edited by: Editorial Board of Journal of Data Acquisition and Processing
P.O. Box 2704, Beijing 100190, P.R. China
Sponsored by: Institute of Computing Technology, CAS & China Computer Federation
Undertaken by: Institute of Computing Technology, CAS
Published by: SCIENCE PRESS, BEIJING, CHINA
Distributed by:
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      1 Jan 2023, Volume 38 Issue 1   
    Article

    1. CHRONIC KIDNEY DISEASE PREDICTION AND DIAGNOSIS USING DIFFERENT MACHINE LEARNING ALGORITHMS
    Mr. Anandkumar A. Sutariya1 and Dr. Dushyantsinh B. Rathod2
    Journal of Data Acquisition and Processing, 2023, 38 (1): 5210-5215 . 

    Abstract

    Chronic Kidney Failure is the medical term for chronic kidney dis-ease. It portrays the moderate disintegration of renal disappointment and how, assuming that constant kidney infection has advanced to a high level stage, a high volume of fluid and undesirable electrolytes may develop in the body. We may see less evidence of chronic renal disease in the early phases. The treatment for chronic kidney disease focuses on slowing down the pro-cess of kidney damage. Without a trace of dialysis or kidney migration, per-sistent renal sickness can advance to the last periods of kidney annihilation, which is inoperable. The focal point of this examination is on early discovery of constant obstructive pneumonia illness utilizing different AI techniques, which are K-Nearest Neighbor, Decision Tree and Bayesian Classifier.

    Keyword

    Chronic Kidney Disease, K-Nearest Neighbor, Decision Tree, and Bayesian Classifier, AI techniques.


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ISSN 1004-9037

         

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