Crunch Mode: Make Early Predictions about Risk of Stroke Using Machine Learning

Abstract

The term “Crunch Mode” refers to periods of intense, prolonged work aimed at meeting deadlines or achieving critical goals. However, extended work in this state can have severe health consequences, including an increased risk of stroke. A stroke occurs when the brain’s blood supply is interrupted or reduced, leading to oxygen and nutrient deprivation that can result in brain cell death. According to the World Health Organization (WHO), stroke is a leading cause of death and disability worldwide. Recognizing early warning signs is crucial in mitigating its impact. This paper employs machine learning techniques to predict the likelihood of an early-stage stroke, as even a mild stroke can cause lasting brain damage, while a severe stroke may be fatal. In this paper, we use machine learning models to predict stroke risk early based on a reliable dataset for stroke prediction that was taken from the Kaggle website.