Predicting Chronic Kidney Disease Using KNN Algorithm

Authors

  • V Mareeswari Department of Computer Science and Engineering, ACS College of Engineering, Bangalore, Karnataka, India
  • Sunita Chalageri Department of Computer Science and Engineering, ACS College of Engineering, Bangalore, Karnataka, India
  • Kavita K Patil Department of Computer Science and Engineering, ACS College of Engineering, Bangalore, Karnataka, India

DOI:

https://doi.org/10.34293/acsjse.v1i2.10

Keywords:

Chronic Kidney Diseases, Disease Registration System, Disease results conclusions

Abstract

Chronic kidney disease (CKD) is a world heath issues, and that also includes damages and can’t filter blood the way it should be. since we cannot predict the early stages of CKD, patience will fail to recognise the disease. Pre detection of CKD will allow patience to get timely facility to ameliorate the progress of the disease. Machine learning models will effectively aid clinician’s progress this goal because of the early and accurate recognition performances. The CKD data set is collected from the University of California Irvine (UCI) Machine Learning Recognition. Multiple Machine and deep learning algorithm used to predict the chronic kidney disease.

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Published

2021-09-09

Issue

Section

Articles