Heart Attack Prediction and Analysis System Using Decision Tree Algorithm

Abstract

Heart Attack Prediction using Machine Learning Technique in Big data analytics has started to play an important role in the healthcare practices and research. heart attack prediction will be found primarily on real-time processing, distributed and real-time classification and distribution, storage so; databases can be easily modified by the doctors. If you know all the attributes related to our health we can check easily how much chance to the Heart attack risk, using the system applications. It was recently used to train classification models. After that using extract the features that is condition to be find to be classified by Decision Tree (DT).Compared to existing; algorithms provides better performance. After classification, performance criteria including accuracy, precision, F-measure is to be calculated. If you are concern about the heart attack risks, you might be referred to a heart specialist. Some attributes are Heart Attack risk factors including which is the High blood pressure, high cholesterol and diabetes, increases your risk even more. Hence we are also checking your symptoms of heart attack and take about prevention.