ISSN (Online) : 2456 - 0774

Email : ijasret@gmail.com

ISSN (Online) 2456 - 0774

A PREDICTION OF HEART DISEASE USING MACHINE LEARNING

Abstract

Abstract— The most frequent type of disease is heart disease. However, thanks to recent technological advancements,machine learning methodologies have accelerated the health sector through multiple studies. As a result, the goal of thisstudy is to create a machine learning Desktop Application for predicting heart disease based on the input parameters.Kaggle provided us with the dataset that we used in our system. We verify the correctness of these models using MachineLearning Algorithms such as Logistic Regression, Naive Bayes, KNN, SVC, Decision Tree Classifier, and Random ForestClassifier. The Random Forest Classifier improves prediction accuracy while using less time. Medical advocates may findthis model useful. As a result, the primary goal of this study work is to forecast.Keywords— machine learning, random forest, algorithm, prediction, heart disease.

Full Text PDF

IMPORTANT DATES 

Submit paper at ijasret@gmail.com

Paper Submission Open For April  20212
UGC indexed in (Old UGC) 2017
Last date for paper submission 30th April, 2022
Deadline Submit Paper any time
Publication of Paper Within 01-02 Days after completing all the formalities
Paper Submission Open For Publication /online Conference 
Publication Fees  
Free for PR Students