Machine learning approach using hierarchical decision- tree projection algorithm to predict the presence of chronic kidney disease
Department of Computer Science, Sri Padmavathi Mahila Vishvavidyalayam (SPMVV), Tirupati, Andhra Pradesh – India.
Research Article
Global Journal of Engineering and Technology Advances, 2021, 08(02), 088–095.
Article DOI: 10.30574/gjeta.2021.8.2.0142
Publication history:
Received on 20 July 2021; revised on 26 August 2021; accepted on 28 August 2021
Abstract:
Chronic Kidney disease is one of the eminent diseases which is commonly seen the patients which the various ailments which results in the step by step failure of kidneys which may result in the fatality of the human. The Chronic Kidney disease which is precisely called as CKD in medical terms is predicted with various symptoms that evolves in the human body. Strategically predicting the CKD using the machine learning algorithm is the challenging proportion. This paper solves the issues of predicting the CKD using the Hierarchical Decision-Tree Projection Algorithm which takes the various clinical study results of the human body into the dataset format and is algorithmically evaluated. Through this method the whole study in completely evaluated with the various parameters which is obtained from the human study. The variations in the whole study with respect to the parametrical correlation are taken into consideration. The results are obtained from each parametrical evaluation and with the results the prediction and presence of the Chronic Kidney disease is evaluated. The Experimental results show the algorithmic evaluations are showing the comparatively high accuracy and performance.
Keywords:
Chronic Kidney Disease; Clinical Evaluation; Hierarchical Decision-Tree Projection Algorithm; Machine Learning
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Copyright © 2021 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0