Expert-System Based Medical Stroke Prevention
Stroke always comes unexpected and the general public is not usually aware of its symptoms. Individuals who have had their first stroke with permanent damage could become an economic burden to their family and a social burden to the society due to their unproductive nature. Stroke could be prevented and its risk factors have been identified. Through a stroke prevention information system, the user could be made more aware of stroke risks and symptoms. An expert system would be able to direct and motivate users to keep themselves healthy therefore preventing first and recurrent strokes. The expert system is built using an inference engine that provides stroke risk level based on information provided by the user. Information collected are self measured blood pressure, cigarettes consumed, amount of physical activity and body mass index. Users are presented with suggested preventive tasks to reduce their stroke risk.
Journal of Computer Science, vol. 9, no. 9, pp. 1099-1105, 2013
Anindito, Bens Pardamean, Robby Christian, Bahtiar Saleh Abbas