Brain Stroke Prediction Using Machine Learning

Abstract

Brain Stroke is considered as the second most common cause of death. We use a set of electronic health records (EHRs) of the patients (43,400 patients) to train our stacked machine learning model to train, test and predict with an accuracy whether the input data points towards a stroke or not. This will help the patient as well as the medical professionals to examine and streamline their work making the process efficient. This study helped us get a result score which was promising enough to continue the research on an extensive level with a professional approach taken here in this paper.