Heart Risk Prediction using Machine Learning : A Literature Review

Abstract

Heart diseases are a leading cause of death among people compared to other diseases. The severity of these diseases has risen significantly in the past few years which has led to the rise of many researchers to present their work in the field of heart risk detection. Machine learning plays an important role in this with the most common machine learning algorithms used for this purpose being Logistic Regression, Naive Bayes, SVM, etc. All these algorithms fall under the classification algorithm category. Data mining plays an important role for feature selection from the dataset. The machine learning algorithms reviewed make use of the same UCI Cleveland dataset.