Coronary Diseases Modeling Of Some Risk Factors Using Artificial Intelligence Techniques

Objective. To estimate the variation in the major risk factors for cardiovascular disease prevalence of smoking obesity and systolic blood pressure we try preventing according coronary heart disease risk factors observed in elderly men and women in the region of Setif Algeria. Participants.100 men and women aged 26 to 86 years for whom the physiological parameters were recorded. These parameters are risk factors for cardiovascular disease. Main outcome measures. The expected analysis was estimated using an artificial intelligence model including the principles of fuzzy logic. Risk factors are inputs of the system and the number of patients with coronary heart disease is output. The observed data recorded from Analysis Central Laboratory of Setif university hospital - Algeria. Results. Factors that promote coronary heart disease are inaccurate and uncertain. The effect of these factors varies from person to person. Their consideration as fuzzy variables is perfectly adequate. Conclusion. A database is established. Fuzzy inference rules are highlighted according to the recorded values. An algorithmic application is established making it possible to read instantly the number likely the person with a coronary disease just by the random introduction of the variables at the input of the system.