Application of Machine Learning Algorithm for Cardiovascular Disease Detection

Abstract

Cardiac disease is a very important topic of study in the medical world and has received a lot of attention worldwide recently. Large quantity of data is available in the medical industry which can be cleaned and used for various purposes. Machine Learning algorithms play a crucial role in predicting of cardiovascular disease. Many researches have been taking place throughout these years in order to handle the early prediction of the diseases. Our research paper checks if the patient is probably going to be diagnosed with any cardiovascular heart disease dependent on their clinical parameters. Throughout this paper, various techniques will be used for data preprocessing and further the performance analysis will be conducted on the seven different classification algorithms so as to foresee if the patient suffers from heart diseases or not. The models used for the study are- Decision Tree Classification, KNN Classifier, Kernel SVM, Support Vector Machine, Logistic Regression, Random Forest Classification, Naïve Bayes and the dataset used comprises of 1025 entries, 14 columns in which there are 13 features and 1 target variable.