Abstract
We propose a neuro-fuzzy hybrid model for the diagnosis of high blood pressure or hypertension to provide a diagnosis as accurate as possible based on intelligent computing techniques, such as neural networks and fuzzy logic. The neuro-fuzzy model uses a modular architecture, which works with different number of layers and different learning parameters so we can have a more accurate modeling. So for the better diagnosis and treatment of hypertension patients, an intelligent and accurate system is needed. In this study, we also design a fuzzy expert system to diagnose blood pressure for different patients. The fuzzy expert system is based on a set of inputs and rules. The input variables for this system are the systolic and diastolic pressures and the output variable is the blood pressures level. It is expected that this proposed neuro-fuzzy hybrid model can provide a faster, cheaper and more accurate result.
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Melin, P., Prado-Arechiga, G. (2018). Design of a Neuro-Fuzzy System for Diagnosis of Arterial Hypertension. In: New Hybrid Intelligent Systems for Diagnosis and Risk Evaluation of Arterial Hypertension. SpringerBriefs in Applied Sciences and Technology(). Springer, Cham. https://doi.org/10.1007/978-3-319-61149-5_3
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DOI: https://doi.org/10.1007/978-3-319-61149-5_3
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