Performance Analysis of Stroke Prediction using Robust Machine Learning Algorithms

Abstract

Stroke is one of the major causes of mortality all over the world. Stroke is caused when the blood flow to the brain is obstructed. The poor blood flow causes death of brain cells and eventually, it may result in death of the person. In this work, three different machine learning algorithms are being used for the prediction of stroke risk, Decision Tree, K Nearest Neighbors and Random Forest. Among these, Random Forest model provides better accuracy of 94.1%. As Compared to traditional methods, using machine learning for the prediction of stroke is convenient and also economical.