Data Mining Techniques to Predict Chronic Kidney Disease and its Stages

  • Authors

    • Ms Nisarga P
    • Ms Kanchana V
    2018-07-15
    https://doi.org/10.14419/ijet.v7i3.10.15623
  • Chronic Kidney Disease, Naïve Bayes, Glomerular Filtration Rate.

  • Abstract

    Chronic Kidney Disease incorporates the state where the kidneys fail to function and reduce the potential to keep a person suffering from the disease healthy. When the condition of the kidneys gets worse, the wastes in the blood are formed in high level. Data mining has been a present pattern for accomplishing analytic outcomes. Colossal measure of un-mined data is gathered by the human services industry so as to find concealed data for powerful analysis and basic leadership. Data mining is the way towards extricating concealed data from gigantic datasets. The goal of our paper is to anticipate CKD utilizing the classification strategy Naïve Bayes. The phases of CKD are anticipated in the light of Glomerular Filtration Rate (GFR).

     

     


     

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  • How to Cite

    Nisarga P, M., & Kanchana V, M. (2018). Data Mining Techniques to Predict Chronic Kidney Disease and its Stages. International Journal of Engineering & Technology, 7(3.10), 27-30. https://doi.org/10.14419/ijet.v7i3.10.15623

    Received date: 2018-07-14

    Accepted date: 2018-07-14

    Published date: 2018-07-15