Exploration of Chronic Kidney Disorder Using Machine Learning Techniques

  • Aruna Kumar Joshi, Vikram Shirol, Prakash Hongal, Vinuta Hiremath

Abstract

Chronic kidney disorder or disease (CKD) is an international fitness affliction that impacts about 10
to 11% of the person populace in the world. It is also recognized as the pinnacle 20 motives of dying
worldwide. Unfortunately, there is no treatment for CKD however, it is feasible to sluggish down its
development and mollify the harm by means of early analysis of the disorder. CKD is a fundamental
public fitness difficulty with rising prevalence. CKD is a serious lifelong circumstance that caused by
means of both kidney pathology or decreased kidney functions. Early prediction and acceptable
redress can per chance stop, or gradual the development of this sickness to end-stage, the place
dialysis or kidney transplantation is the solely way to keep patient’s life.CKD is a disease which
doesn’t indicates signs and symptoms at all or in some instances it doesn’t exhibit any disorder
particular signs it is difficult to predict, realize and forestall such a sickness and this should be lead to
completely fitness damage, however few of desktop getting to know techniques are explored consisting
of K-nearest neighbour (KNN),support vector machine (SVM), logistic regression (LR), and Decision
tree classifiers, etc. kidney disorder prediction and analysis. By the usage of records of CKD suffers
with 14 attributes and four hundred report we are going to use a range of methods as referred to
above to construct a mannequin with most accuracy of predicting whether or not CKD or no longer
and if sure then its severity.

Published
2020-05-20
How to Cite
Aruna Kumar Joshi, Vikram Shirol, Prakash Hongal, Vinuta Hiremath. (2020). Exploration of Chronic Kidney Disorder Using Machine Learning Techniques. International Journal of Advanced Science and Technology, 29(9s), 5972-5978. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/18792