A Review of Predictive Systems for Patients at Risk of Developing Stroke

Stroke remains one of the leading causes of death worldwide. It is usually associated with a build-up of fatty deposits inside the arteries which increases the risk of blood clotting. The unannounced nature of the disease when it strikes has posed a major challenge in the health sector. Poor medical facilities, insufficient information on how to accurately diagnose stroke, late identification of the disease by the patients due to being ignorant of the disease are some of the reasons for the increasing mortality rate due it. The application of data mining technique in the field of medicine has brought about positive development in the area of diagnosing, prediction and deeply understanding of healthcare data. This study considers some of the Predictive Models developed using some data mining approaches to predict patients at risk of developing stroke in order for other researchers to build on.