Visualization and Prediction of Heart Disease using Big Data Analytics

Heart disease is the leading cause of deaths worldwide. According to a study published in 2016, one out of every four fatalities in India is caused by cardiovascular disease, which, if not treated properly and immediately, can cause serious health difficulties in patients. Millions of people's lives may be saved if this life-threatening condition could be detected early. This paper proposes a legitimate fitness state detection approach with a heart disease use-case combining machine learning models such as K-Nearest Neighbors, Random Forest algo, and other ensemble learning approaches. This strategy focuses on using machine learning models to predict cardiac problems using real-time data. Stacking CV Classifier with KNN as meta classifier surpasses the other classifiers used in the study with an accuracy rate of 93.39% when using the ensemble learning approach on the data.