Abstract
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.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 5th Brazilian Technology Symposium - Emerging Trends, Issues, and Challenges in the Brazilian Technology |
| Editors | Yuzo Iano, Rangel Arthur, Osamu Saotome, Guillermo Kemper, Ana Carolina Borges Monteiro |
| Publisher | Springer Science and Business Media Deutschland GmbH |
| Pages | 169-175 |
| Number of pages | 7 |
| ISBN (Print) | 9783030575656 |
| DOIs | |
| Publication status | Published - 2021 |
| Event | 5th Brazilian Technology Symposium, BTSym 2019 - Campinas, Brazil Duration: Oct 22 2019 → Oct 24 2019 |
Publication series
| Name | Smart Innovation, Systems and Technologies |
|---|---|
| Volume | 202 |
| ISSN (Print) | 2190-3018 |
| ISSN (Electronic) | 2190-3026 |
Conference
| Conference | 5th Brazilian Technology Symposium, BTSym 2019 |
|---|---|
| Country/Territory | Brazil |
| City | Campinas |
| Period | 10/22/19 → 10/24/19 |
Bibliographical note
Publisher Copyright:© 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.
ASJC Scopus Subject Areas
- General Decision Sciences
- General Computer Science
