Analysis and Prediction of Stroke using Machine Learning Algorithms

Abstract

Stroke is a medical emergency that occurs when a section of the brain’s blood supply is cut off. The brain cells die when they are deprived of the oxygen and glucose needed for their survival. It is the world’s second prevalent disease and can be fatal if it is not treated on time. An early intervention and prediction could prevent the occurrence of stroke. Machine learning algorithms are transforming the healthcare and is widely used in early diagnosis of diseases. This work focuses on the prediction of the occurrence of stroke at an early stage using machine learning algorithms. This paper establishes Ada Boost’s superiority over other well-known classification algorithms for early stroke prediction.