Stroke Prediction Using Machine Learning Methodology

Abstract

Stroke is a major disease leading to death in adults and elderly people, as well as disability. Rapid detection of stroke is very difficult because the cause and cause of the onset are different for each individual. In this proposed model, we develop model stroke prediction using machine learning approach and implement a system on WHO provide dataset. The most efficient and accurate variables required to predict stroke in an individual is obtained through Feature Selection and as per the variables gained, the features which influence the disease prognosis is obtained. Predictive modelling is performed on this processed data with various classification models such as Random Forest, Decision tree, Logistic Regression and Support Vector Machines. The web application is made to process user inputs and predict the occurrence of stroke using the most accurate model.