Journal of Computing and Natural Science


A Detailed Analysis on Kidney and Heart Disease Prediction using Machine Learning



Journal of Computing and Natural Science

Received On : 25 October 2020

Revised On : 25 November 2020

Accepted On : 28 December 2020

Published On : 05 January 2021

Volume 01, Issue 01

Pages : 009-014


Abstract


Detection of disease at earlier stages is the most challenging one. Datasets of different diseases are available online with different number of features corresponding to a particular disease. Many dimensionalities reduction and feature extraction techniques are used nowadays to reduce the number of features in dataset and finding the most appropriate ones. This paper explores the difference in performance of different machine learning models using Principal Component Analysis dimensionality reduction technique on the datasets of Chronic kidney disease and Cardiovascular disease. Further, the authors apply Logistic Regression, K Nearest Neighbour, Naïve Bayes, Support Vector Machine and Random Forest Model on the datasets and compare the performance of the model with and without PCA. A key challenge in the field of data mining and machine learning is building accurate and computationally efficient classifiers for medical applications. With an accuracy of 100% in chronic kidney disease and 85% for heart disease, KNN classifier and logistic regression were revealed to be the most optimal method of predictions for kidney and heart disease respectively.


Keywords


Kidney Disease, Cardiovascular Disease, Logistic Regression, Support Vector Machine, Random Forest.


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Acknowledgements


We would like to thank Reviewers for taking the time and effort necessary to review the manuscript. We sincerely appreciate all valuable comments and suggestions, which helped us to improve the quality of the manuscript.


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No funding was received to assist with the preparation of this manuscript.


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The authors have no conflicts of interest to declare that are relevant to the content of this article.


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Cite this article


Claire Salkar, “A Detailed Analysis on Kidney and Heart Disease Prediction using Machine Learning”, Journal of Computing and Natural Science, vol.1, no.1, pp. 009-014, January 2021. doi: 10.53759/181X/JCNS202101003.


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© 2021 Claire Salkar. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.