Early screening of incidence coronary heart disease based on risk factor using fuzzy rule system
Wiharto Wiharto · International Journal of ADVANCED AND APPLIED SCIENCES · 2017
A thorough examination in the context of the diagnosis of coronary heart disease requires a relatively high cost.To reduce the cost of the diagnosis can be done gradually, preceded by the initial screening based on risk factors.Initial screening can be done using a model that has been developed.Unfortunately the development of a model screening, reference to specific populations, such as the Framingham risk scores (FRS), so sometimes does not correspond to other populations.This study proposes a model of screening by combining FRS with artificial intelligence techniques, for initial screening on the risk of coronary heart disease.The research method is divided into several stages, firstly the selection of an attribute of risk factors.The second, modeling of the attribute into a fuzzy rule with reference to a standard FRS.The third, modeling of inference using Mamdani method, and the last of analyzing system performance.The test results show that the model proposed system has the ability, if positive patients tested, capable of producing a really positive output of coronary heart disease in the amount of sensitivity that is 91.37%.The performance is relatively better than a number of previous studies, with only requires an examination of the four attributes, namely age, sex, cholesterol and systolic blood pressure.