Publications

Abstract : This paper provides an effective method for detecting stroke. R language inRStudio is used to conduct data analysis and for the construction of a prediction application. Making a random user be able to test themselves for stroke is the primary objective of this project. The web application and the data analysis parts are made to work on the patients’ characteristics data. The stroke training and test datasets are gathered and exploratory data analysis is performed. 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 modeling 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.