A technological solution to identify the level of risk to be diagnosed with type 2 diabetes mellitus using wearables

Descripción del Articulo

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.
Detalles Bibliográficos
Autores: Nuñovero, Daniela, Rodríguez, Ernesto, Armas, Jimmy, Gonzalez, Paola
Formato: artículo
Fecha de Publicación:2021
Institución:Universidad Peruana de Ciencias Aplicadas
Repositorio:UPC-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorioacademico.upc.edu.pe:10757/653787
Enlace del recurso:https://doi.org/10.1007/978-3-030-57566-3_17
http://hdl.handle.net/10757/653787
Nivel de acceso:acceso abierto
Materia:Primary prevention
Type 2 diabetes mellitus
Wearable
Computer aided diagnosis
Noninvasive medical procedures
Predictive analytics
Risk assessment
Classification algorithm
Noninvasive methods
Preventive treatments
https://purl.org/pe-repo/ocde/ford#2.11.00
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spelling 12ea5a7e21d95f058b99428d71f9e04e3006b71afca77b1a426b2d316ea8f51f224300b762e0d7f98e2d8a64bec0c6492e6061f1e9e383578080fdbc8d0abd6dd9cNuñovero, DanielaRodríguez, ErnestoArmas, JimmyGonzalez, Paola2021-01-07T16:54:31Z2021-01-07T16:54:31Z2021-01-0121903018https://doi.org/10.1007/978-3-030-57566-3_17http://hdl.handle.net/10757/65378721903026Smart Innovation, Systems and Technologies2-s2.0-85098159469SCOPUS_ID:850981594690000 0001 2196 144XEl texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.This paper proposes a technological solution using a predictive analysis model to identify and reduce the level of risk for type 2 diabetes mellitus (T2DM) through a wearable device. Our proposal is based on previous models that use the auto-classification algorithm together with the addition of new risk factors, which provide a greater contribution to the results of the presumptive diagnosis of the user who wants to check his level of risk. The purpose is the primary prevention of type 2 diabetes mellitus by a non-invasive method composed of the phases: (1) Capture and storage of risk factors; (2) Predictive analysis model; (3) Presumptive results and recommendations; and (4) Preventive treatment. The main contribution is in the development of the proposed application.Revisión por paresengSpringer Science and Business Media Deutschland GmbHhttps://www.scopus.com/record/display.uri?eid=2-s2.0-85098159469&doi=10.1007%2f978-3-030-57566-3_17&origin=inward&txGid=1d43fb6903477dfb05950f1ad8911187info:eu-repo/semantics/openAccessRepositorio Academico - UPCUniversidad Peruana de Ciencias Aplicadas (UPC)Smart Innovation, Systems and Technologies202169175reponame:UPC-Institucionalinstname:Universidad Peruana de Ciencias Aplicadasinstacron:UPCPrimary preventionType 2 diabetes mellitusWearableComputer aided diagnosisNoninvasive medical proceduresPredictive analyticsRisk assessmentClassification algorithmNoninvasive methodsPreventive treatmentshttps://purl.org/pe-repo/ocde/ford#2.11.00A technological solution to identify the level of risk to be diagnosed with type 2 diabetes mellitus using wearablesinfo:eu-repo/semantics/articlehttp://purl.org/coar/version/c_970fb48d4fbd8a2514PublicationLICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://upc.dspace7.openrepository.com/bitstreams/85534b07-7e73-5b41-9e19-b88451a8b550/download8a4605be74aa9ea9d79846c1fba20a33MD5110757/653787oai:upc.dspace7.openrepository.com:10757/6537872026-02-17 17:49:15.508metadata.onlyhttps://upc.dspace7.openrepository.comRepositorio académico upcrepositorioacademico@upc.edu.pe
dc.title.en_US.fl_str_mv A technological solution to identify the level of risk to be diagnosed with type 2 diabetes mellitus using wearables
title A technological solution to identify the level of risk to be diagnosed with type 2 diabetes mellitus using wearables
spellingShingle A technological solution to identify the level of risk to be diagnosed with type 2 diabetes mellitus using wearables
Nuñovero, Daniela
Primary prevention
Type 2 diabetes mellitus
Wearable
Computer aided diagnosis
Noninvasive medical procedures
Predictive analytics
Risk assessment
Classification algorithm
Noninvasive methods
Preventive treatments
https://purl.org/pe-repo/ocde/ford#2.11.00
title_short A technological solution to identify the level of risk to be diagnosed with type 2 diabetes mellitus using wearables
title_full A technological solution to identify the level of risk to be diagnosed with type 2 diabetes mellitus using wearables
title_fullStr A technological solution to identify the level of risk to be diagnosed with type 2 diabetes mellitus using wearables
title_full_unstemmed A technological solution to identify the level of risk to be diagnosed with type 2 diabetes mellitus using wearables
title_sort A technological solution to identify the level of risk to be diagnosed with type 2 diabetes mellitus using wearables
author Nuñovero, Daniela
author_facet Nuñovero, Daniela
Rodríguez, Ernesto
Armas, Jimmy
Gonzalez, Paola
author_role author
author2 Rodríguez, Ernesto
Armas, Jimmy
Gonzalez, Paola
author2_role author
author
author
dc.contributor.author.fl_str_mv Nuñovero, Daniela
Rodríguez, Ernesto
Armas, Jimmy
Gonzalez, Paola
dc.subject.en_US.fl_str_mv Primary prevention
Type 2 diabetes mellitus
Wearable
Computer aided diagnosis
Noninvasive medical procedures
Predictive analytics
Risk assessment
Classification algorithm
Noninvasive methods
Preventive treatments
topic Primary prevention
Type 2 diabetes mellitus
Wearable
Computer aided diagnosis
Noninvasive medical procedures
Predictive analytics
Risk assessment
Classification algorithm
Noninvasive methods
Preventive treatments
https://purl.org/pe-repo/ocde/ford#2.11.00
dc.subject.ocde.none.fl_str_mv https://purl.org/pe-repo/ocde/ford#2.11.00
description El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.
publishDate 2021
dc.date.accessioned.none.fl_str_mv 2021-01-07T16:54:31Z
dc.date.available.none.fl_str_mv 2021-01-07T16:54:31Z
dc.date.issued.fl_str_mv 2021-01-01
dc.type.es_PE.fl_str_mv info:eu-repo/semantics/article
dc.type.version.none.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a2514
format article
dc.identifier.issn.none.fl_str_mv 21903018
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1007/978-3-030-57566-3_17
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/10757/653787
dc.identifier.eissn.none.fl_str_mv 21903026
dc.identifier.journal.en_US.fl_str_mv Smart Innovation, Systems and Technologies
dc.identifier.eid.none.fl_str_mv 2-s2.0-85098159469
dc.identifier.scopusid.none.fl_str_mv SCOPUS_ID:85098159469
dc.identifier.isni.none.fl_str_mv 0000 0001 2196 144X
identifier_str_mv 21903018
21903026
Smart Innovation, Systems and Technologies
2-s2.0-85098159469
SCOPUS_ID:85098159469
0000 0001 2196 144X
url https://doi.org/10.1007/978-3-030-57566-3_17
http://hdl.handle.net/10757/653787
dc.language.iso.en_US.fl_str_mv eng
language eng
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dc.rights.en_US.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Springer Science and Business Media Deutschland GmbH
publisher.none.fl_str_mv Springer Science and Business Media Deutschland GmbH
dc.source.es_PE.fl_str_mv Repositorio Academico - UPC
Universidad Peruana de Ciencias Aplicadas (UPC)
dc.source.none.fl_str_mv reponame:UPC-Institucional
instname:Universidad Peruana de Ciencias Aplicadas
instacron:UPC
instname_str Universidad Peruana de Ciencias Aplicadas
instacron_str UPC
institution UPC
reponame_str UPC-Institucional
collection UPC-Institucional
dc.source.journaltitle.none.fl_str_mv Smart Innovation, Systems and Technologies
dc.source.volume.none.fl_str_mv 202
dc.source.beginpage.none.fl_str_mv 169
dc.source.endpage.none.fl_str_mv 175
bitstream.url.fl_str_mv https://upc.dspace7.openrepository.com/bitstreams/85534b07-7e73-5b41-9e19-b88451a8b550/download
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A technological solution to identify the level of risk to be diagnosed with type 2 diabetes mellitus using wearables
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