dc.date.accessioned2019-08-25T19:29:29Z
dc.date.accessioned2023-05-31T19:05:19Z
dc.date.available2019-08-25T19:29:29Z
dc.date.available2023-05-31T19:05:19Z
dc.date.created2019-08-25T19:29:29Z
dc.date.issued2016-10
dc.identifierNieto Chaupis, H., & Matta Solis, H. (Octubre, 2016). Evaluation of type-2 diabetes progress in adult patients by using predictive algorithms. En Ecuador Technical Chapters Meeting (ETCM), Ecuador.
dc.identifierhttp://repositorio.uch.edu.pe/handle/uch/368
dc.identifierhttps://ieeexplore.ieee.org/document/7750811
dc.identifierhttp://dx.doi.org/10.1109/ETCM.2016.7750811
dc.identifier10.1109/ETCM.2016.7750811
dc.identifierIEEE Ecuador Technical Chapters Meeting, ETCM
dc.identifier2-s2.0-85007020611
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/6495686
dc.description.abstractWe used computational simulation inside a teleconsult scheme to predict the levels of diabetes progress of a sample of type-2 diabetes adult patients. Concretely, we have used computational algorithms to estimate the fraction of patients which would acquire diabetes complications such as necrosis, nephropathy and unexpected cardiovascular events. For this end, we have constructed a general function G which gives account of the behavior of glucose in time, but it is depending of up to 4 free parameters representing in somewhat: Diet, pharmacology, attitude of patient against the progress of disease, and a random number by the which it might be consistent with the binge eating disorder. From the results of this paper around 5±1 patients might increase their probabilities to pass to the subsequent diabetes such diabetic nephropathy.
dc.languageeng
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relationIEEE Ecuador Technical Chapters Meeting, ETCM 2016
dc.relationinfo:eu-repo/semantics/article
dc.rightsinfo:eu-repo/semantics/embargoedAccess
dc.sourceRepositorio Institucional - UCH
dc.sourceUniversidad de Ciencias y Humanidades
dc.subjectCardiovascular event
dc.subjectComputational algorithm
dc.subjectComputational simulation
dc.subjectDiabetic nephropathy
dc.subjectEating disorders
dc.subjectGeneral functions
dc.subjectPredictive algorithms
dc.subjectType-2 diabetes
dc.titleEvaluation of type-2 diabetes progress in adult patients by using predictive algorithms
dc.typeinfo:eu-repo/semantics/conferenceObject


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