Evaluation of type-2 diabetes progress in adult patients by using predictive algorithms
Descripción del Articulo
We 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, n...
Autores: | , |
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Formato: | objeto de conferencia |
Fecha de Publicación: | 2016 |
Institución: | Universidad de Ciencias y Humanidades |
Repositorio: | UCH-Institucional |
Lenguaje: | inglés |
OAI Identifier: | oai:repositorio.uch.edu.pe:uch/368 |
Enlace del recurso: | http://repositorio.uch.edu.pe/handle/uch/368 https://ieeexplore.ieee.org/document/7750811 http://dx.doi.org/10.1109/ETCM.2016.7750811 |
Nivel de acceso: | acceso embargado |
Materia: | Cardiovascular event Computational algorithm Computational simulation Diabetic nephropathy Eating disorders General functions Predictive algorithms Type-2 diabetes |
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Nieto Chaupis, HuberMatta Solis, Hernán12 October 2016 through 14 October 20162019-08-25T19:29:29Z2019-08-25T19:29:29Z2016-10Nieto 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.http://repositorio.uch.edu.pe/handle/uch/368https://ieeexplore.ieee.org/document/7750811http://dx.doi.org/10.1109/ETCM.2016.775081110.1109/ETCM.2016.7750811IEEE Ecuador Technical Chapters Meeting, ETCM2-s2.0-85007020611We 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.Submitted by sistemas uch (sistemas@uch.edu.pe) on 2019-08-25T19:29:29Z No. of bitstreams: 1 REPOSITORIO.pdf: 29656 bytes, checksum: 04319d67592b306412ce804f495f0004 (MD5)Made available in DSpace on 2019-08-25T19:29:29Z (GMT). No. of bitstreams: 1 REPOSITORIO.pdf: 29656 bytes, checksum: 04319d67592b306412ce804f495f0004 (MD5) Previous issue date: 2016-10engInstitute of Electrical and Electronics Engineers Inc.info:eu-repo/semantics/articleIEEE Ecuador Technical Chapters Meeting, ETCM 2016info:eu-repo/semantics/embargoedAccessRepositorio Institucional - UCHUniversidad de Ciencias y Humanidadesreponame:UCH-Institucionalinstname:Universidad de Ciencias y Humanidadesinstacron:UCHCardiovascular eventComputational algorithmComputational simulationDiabetic nephropathyEating disordersGeneral functionsPredictive algorithmsType-2 diabetesEvaluation of type-2 diabetes progress in adult patients by using predictive algorithmsinfo:eu-repo/semantics/conferenceObjectuch/368oai:repositorio.uch.edu.pe:uch/3682019-12-20 18:34:00.783Repositorio UCHuch.dspace@gmail.com |
dc.title.en_PE.fl_str_mv |
Evaluation of type-2 diabetes progress in adult patients by using predictive algorithms |
title |
Evaluation of type-2 diabetes progress in adult patients by using predictive algorithms |
spellingShingle |
Evaluation of type-2 diabetes progress in adult patients by using predictive algorithms Nieto Chaupis, Huber Cardiovascular event Computational algorithm Computational simulation Diabetic nephropathy Eating disorders General functions Predictive algorithms Type-2 diabetes |
title_short |
Evaluation of type-2 diabetes progress in adult patients by using predictive algorithms |
title_full |
Evaluation of type-2 diabetes progress in adult patients by using predictive algorithms |
title_fullStr |
Evaluation of type-2 diabetes progress in adult patients by using predictive algorithms |
title_full_unstemmed |
Evaluation of type-2 diabetes progress in adult patients by using predictive algorithms |
title_sort |
Evaluation of type-2 diabetes progress in adult patients by using predictive algorithms |
author |
Nieto Chaupis, Huber |
author_facet |
Nieto Chaupis, Huber Matta Solis, Hernán |
author_role |
author |
author2 |
Matta Solis, Hernán |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Nieto Chaupis, Huber Matta Solis, Hernán |
dc.subject.en.fl_str_mv |
Cardiovascular event Computational algorithm Computational simulation Diabetic nephropathy Eating disorders General functions Predictive algorithms Type-2 diabetes |
topic |
Cardiovascular event Computational algorithm Computational simulation Diabetic nephropathy Eating disorders General functions Predictive algorithms Type-2 diabetes |
description |
We 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. |
publishDate |
2016 |
dc.date.accessioned.none.fl_str_mv |
2019-08-25T19:29:29Z |
dc.date.available.none.fl_str_mv |
2019-08-25T19:29:29Z |
dc.date.issued.fl_str_mv |
2016-10 |
dc.type.en_PE.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
dc.identifier.citation.en_PE.fl_str_mv |
Nieto 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.identifier.uri.none.fl_str_mv |
http://repositorio.uch.edu.pe/handle/uch/368 https://ieeexplore.ieee.org/document/7750811 http://dx.doi.org/10.1109/ETCM.2016.7750811 |
dc.identifier.doi.en_PE.fl_str_mv |
10.1109/ETCM.2016.7750811 |
dc.identifier.journal.en_PE.fl_str_mv |
IEEE Ecuador Technical Chapters Meeting, ETCM |
dc.identifier.scopus.none.fl_str_mv |
2-s2.0-85007020611 |
identifier_str_mv |
Nieto 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. 10.1109/ETCM.2016.7750811 IEEE Ecuador Technical Chapters Meeting, ETCM 2-s2.0-85007020611 |
url |
http://repositorio.uch.edu.pe/handle/uch/368 https://ieeexplore.ieee.org/document/7750811 http://dx.doi.org/10.1109/ETCM.2016.7750811 |
dc.language.iso.none.fl_str_mv |
eng |
language |
eng |
dc.relation.en_PE.fl_str_mv |
info:eu-repo/semantics/article |
dc.relation.ispartof.none.fl_str_mv |
IEEE Ecuador Technical Chapters Meeting, ETCM 2016 |
dc.rights.en_PE.fl_str_mv |
info:eu-repo/semantics/embargoedAccess |
eu_rights_str_mv |
embargoedAccess |
dc.coverage.temporal.none.fl_str_mv |
12 October 2016 through 14 October 2016 |
dc.publisher.en_PE.fl_str_mv |
Institute of Electrical and Electronics Engineers Inc. |
dc.source.en_PE.fl_str_mv |
Repositorio Institucional - UCH Universidad de Ciencias y Humanidades |
dc.source.none.fl_str_mv |
reponame:UCH-Institucional instname:Universidad de Ciencias y Humanidades instacron:UCH |
instname_str |
Universidad de Ciencias y Humanidades |
instacron_str |
UCH |
institution |
UCH |
reponame_str |
UCH-Institucional |
collection |
UCH-Institucional |
repository.name.fl_str_mv |
Repositorio UCH |
repository.mail.fl_str_mv |
uch.dspace@gmail.com |
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1835549007332507648 |
score |
13.814859 |
Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).