A Technological Solution to Identify the Level of Risk to Be Diagnosed with Type 2 Diabetes Mellitus Using Wearables
Fecha
2021-01-01Registro en:
21903018
10.1007/978-3-030-57566-3_17
21903026
Smart Innovation, Systems and Technologies
2-s2.0-85098159469
SCOPUS_ID:85098159469
0000 0001 2196 144X
Autor
Nuñovero, Daniela
Rodríguez, Ernesto
Armas, Jimmy
Gonzalez, Paola
Institución
Resumen
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.