Exploration of Chronic Kidney Disorder Using Machine Learning Techniques - Aruna Kumar Joshi, Vikram Shirol, Prakash Hongal, Vinuta Hiremath (International Journal of Advanced Science and Technology, 2020)
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.