A hybrid intelligent system model for hypertension diagnosis

Abstract

A hybrid intelligent system is made of a powerful combination of soft computing techniques for reducing the complexity in solving difficult problems. Nowadays hypertension (high blood pressure) has a high prevalence in the world population and is the number one cause of mortality in Mexico, and this is why it is called a silent killer because it often has no symptoms. We design in this paper a hybrid model using modular neural networks, and as response integrator we use fuzzy systems to provide an accurate diagnosis of hypertension, so we can prevent future diseases in people based on the systolic pressure, diastolic pressure, and pulse of patients with ages between 15 and 95 years.