El 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 pares
| Identifer | oai:union.ndltd.org:PERUUPC/oai:repositorioacademico.upc.edu.pe:10757/653787 |
| Date | 01 January 2021 |
| Creators | Nuñovero, Daniela, Rodríguez, Ernesto, Armas, Jimmy, Gonzalez, Paola |
| Source Sets | Universidad Peruana de Ciencias Aplicadas (UPC) |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/article |
| Source | Repositorio Academico - UPC, Universidad Peruana de Ciencias Aplicadas (UPC), Smart Innovation, Systems and Technologies, 202, 169, 175 |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | https://www.scopus.com/record/display.uri?eid=2-s2.0-85098159469&doi=10.1007%2f978-3-030-57566-3_17&origin=inward&txGid=1d43fb6903477dfb05950f1ad8911187 |
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