Disease Prediction using Machine Learning


Authors : Anika Shreya Pawar

Volume/Issue : Volume 7 - 2022, Issue 8 - August

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

Scribd : https://bit.ly/3dfcof7

DOI : https://doi.org/10.5281/zenodo.7073448

Abstract : Machine learning (ML) is an artificial intelligence (AI) technique that facilitates the improvement of predictability in software applications without requiring explicit programming. Data from the past is used to predict new outcomes using machine learning algorithms. During the course of this paper, we used four machine learning algorithms: Logistic Regression, Support Vector Machine, Decision Tree, and Gradient Boosting. Our chosen algorithms were applied to five datasets from the healthcare domain, in which we were able to predict kidney disease, liver disease, breast cancer predictions, heart diseases, and diabetes predictions.

Keywords : Machine Learning; kidney; heart; liver; breast- cancer; diabetes; svm; linear regression; decision tree; gradient boosting.

Machine learning (ML) is an artificial intelligence (AI) technique that facilitates the improvement of predictability in software applications without requiring explicit programming. Data from the past is used to predict new outcomes using machine learning algorithms. During the course of this paper, we used four machine learning algorithms: Logistic Regression, Support Vector Machine, Decision Tree, and Gradient Boosting. Our chosen algorithms were applied to five datasets from the healthcare domain, in which we were able to predict kidney disease, liver disease, breast cancer predictions, heart diseases, and diabetes predictions.

Keywords : Machine Learning; kidney; heart; liver; breast- cancer; diabetes; svm; linear regression; decision tree; gradient boosting.

Never miss an update from Papermashup

Get notified about the latest tutorials and downloads.

Subscribe by Email

Get alerts directly into your inbox after each post and stay updated.
Subscribe
OR

Subscribe by RSS

Add our RSS to your feedreader to get regular updates from us.
Subscribe