Smart Health Prediction System


Authors : Vivek Joshi; Shipra Goswami; Shalini Goel

Volume/Issue : Volume 7 - 2022, Issue 4 - April

Google Scholar : https://bit.ly/3IIfn9N

Scribd : https://bit.ly/3MEk331

DOI : https://doi.org/10.5281/zenodo.6569964

Abstract : With the promises of predictive analysis in machine learning algorithms, prediction of future is no longer a difficult task. Many efforts have already been done to obtain useful knowledge from it. In this paper, we will apply five machine learning algorithms on three different set of medical data. The objective of this research paper is to predict heart disease, diabetes and liver disease by using different machine learning algorithms that are Naïve Bayes Algorithm, Support Vector Machine, Decision Tree, KNN, Logistic Regression and find the most efficient one.

Keywords : Machine Learning, Naïve Bayes Algorithm, SVM, KNN, Regression, Decision Tree and Logistic Regression.

With the promises of predictive analysis in machine learning algorithms, prediction of future is no longer a difficult task. Many efforts have already been done to obtain useful knowledge from it. In this paper, we will apply five machine learning algorithms on three different set of medical data. The objective of this research paper is to predict heart disease, diabetes and liver disease by using different machine learning algorithms that are Naïve Bayes Algorithm, Support Vector Machine, Decision Tree, KNN, Logistic Regression and find the most efficient one.

Keywords : Machine Learning, Naïve Bayes Algorithm, SVM, KNN, Regression, Decision Tree and Logistic Regression.

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