Predicting risks of developing heart diseases using machine learning algorithms

Heart diseases are known by many names around the world such as arrhythmias, heart failure, cardiac arrest, cardiovascular diseases, etc. People around the world are victims of developing a risk to catch these diseases in the long term go. Keeping these risk-developing patterns in mind, it is possible to train a machine in predicting whether a person will develop a heart condition in the next ten years. The machine learning models used in this paper are decision trees, random forests, KNN, and K-Means. This research paper aims to explore the application of machine learning techniques to better identify heart diseases in advance without the interference of any medical practitioner.