Heart Disease Detection Using Machine Learning

Abstract

This paper analyzes the detection of heart disease using machine learning algorithms and python programming. Over the post decades, heart disease is common and dangerous disease caused by fat containment. This disease occurs due to over pressure in the human body. Using different types of parameters in the dataset we can predict the cardiac-disease. We have observed a dataset consists of 12 parameters and 70000 individual data values[5] to analyze the performance of patients. The main objective of the paper is to get a better accuracy to detect the heart-disease using algorithms in which the target output counts that a person having heart disease or not.

Heart Disease Detection Using Machine Learning and Deep Learning

“…In [4] used a dataset with 70,000 records and 11 features for Heart Disease Detection. KNN, Random Forest Classifier, Decision Tree and SVM are used.…”