Abstract
In this paper, a method is proposed to diagnose the blood pressure of a patient (Astolic pressure, diastolic pressure, and pulse). This method consists of a modular neural network and its response with average integration. The proposed approach consists on applying these methods to find the best architecture of the modular neural network and the lowest prediction error. Simulations results show that the modular network produces a good diagnostic of the blood pressure of a patient.
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We would like to express our gratitude to the CONACYT, Tijuana Institute of Technology for the facilities and resources granted for the development of this research.
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Pulido, M., Melin, P., Prado-Arechiga, G. (2017). A New Method Based on Modular Neural Network for Arterial Hypertension Diagnosis. In: Melin, P., Castillo, O., Kacprzyk, J. (eds) Nature-Inspired Design of Hybrid Intelligent Systems. Studies in Computational Intelligence, vol 667. Springer, Cham. https://doi.org/10.1007/978-3-319-47054-2_13
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DOI: https://doi.org/10.1007/978-3-319-47054-2_13
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