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A computational technique to predict the level of glucose of a diabetic patient with uncertainty in the short term

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A computational technique to predict the level of glucose of a diabetic patient with uncertainty in the short term

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Burgos Simon, C.; Cervigón, C.; Hidalgo, J.; Villanueva Micó, RJ. (2019). A computational technique to predict the level of glucose of a diabetic patient with uncertainty in the short term. Computational and Mathematical Methods. 2(2):1-11. https://doi.org/10.1002/cmm4.1064

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/151156

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Title: A computational technique to predict the level of glucose of a diabetic patient with uncertainty in the short term
Author: Burgos Simon, Clara Cervigón, Carlos Hidalgo, José-Ignacio Villanueva Micó, Rafael Jacinto
UPV Unit: Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada
Universitat Politècnica de València. Instituto Universitario de Matemática Multidisciplinar - Institut Universitari de Matemàtica Multidisciplinària
Issued date:
Abstract:
[EN] On advanced stages of the disease, diabetic patients have to inject insulin doses to maintain blood glucose levels inside of a healthy range. The decision of how much insulin is injected implies somehow to predict the ...[+]
Copyrigths: Reserva de todos los derechos
Source:
Computational and Mathematical Methods. (eissn: 2577-7408 )
DOI: 10.1002/cmm4.1064
Publisher:
John Wiley & Sons
Publisher version: https://doi.org/10.1002/cmm4.1064
Project ID:
MINECO/RTI2018-095180-B-I00
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2017-89664-P/ES/PROBLEMAS DINAMICOS CON INCERTIDUMBRE SIMULABLE: MODELIZACION MATEMATICA, ANALISIS, COMPUTACION Y APLICACIONES/
Thanks:
This work has been partially supported by the Spanish Ministerio de Economía y Competitividad under grant MTM2017-89664-P and RTI2018-095180-B-I00 and by Fundación Eugenio Rodriguez Pascual 2019 -GLENO Project
Type: Artículo

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