Artificial intelligence methodologies and their application to diabetes

Rigla Cros, Mercedes and García Sáez, Gema and Pons Pons, Belén and Hernando Pérez, María Elena (2017). Artificial intelligence methodologies and their application to diabetes. "Journal of diabetes science and technology", v. 11 (n. 3); pp. 1-8. ISSN 1932-2968. https://doi.org/10.1177/1932296817710475.

Description

Title: Artificial intelligence methodologies and their application to diabetes
Author/s:
  • Rigla Cros, Mercedes
  • García Sáez, Gema
  • Pons Pons, Belén
  • Hernando Pérez, María Elena
Item Type: Article
Título de Revista/Publicación: Journal of diabetes science and technology
Date: May 2017
ISSN: 1932-2968
Volume: 11
Subjects:
Freetext Keywords: artificial intelligence, decision support, diabetes, machine learning
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Tecnología Fotónica y Bioingeniería
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

In the past decade diabetes management has been transformed by the addition of continuous glucose monitoring and insulin pump data. More recently, a wide variety of functions and physiologic variables, such as heart rate, hours of sleep, number of steps walked and movement, have been available through wristbands or watches. New data, hydration, geolocation, and barometric pressure, among others, will be incorporated in the future. All these parameters, when analyzed, can be helpful for patients and doctors' decision support. Similar new scenarios have appeared in most medical fields, in such a way that in recent years, there has been an increased interest in the development and application of the methods of artificial intelligence (AI) to decision support and knowledge acquisition. Multidisciplinary research teams integrated by computer engineers and doctors are more and more frequent, mirroring the need of cooperation in this new topic. AI, as a science, can be defined as the ability to make computers do things that would require intelligence if done by humans. Increasingly, diabetes-related journals have been incorporating publications focused on AI tools applied to diabetes. In summary, diabetes management scenarios have suffered a deep transformation that forces diabetologists to incorporate skills from new areas. This recently needed knowledge includes AI tools, which have become part of the diabetes health care. The aim of this article is to explain in an easy and plane way the most used AI methodologies to promote the implication of health care providers?doctors and nurses?in this field.

More information

Item ID: 49927
DC Identifier: http://oa.upm.es/49927/
OAI Identifier: oai:oa.upm.es:49927
DOI: 10.1177/1932296817710475
Official URL: http://journals.sagepub.com/doi/10.1177/1932296817710475#
Deposited by: Memoria Investigacion
Deposited on: 17 Apr 2018 17:00
Last Modified: 30 May 2019 10:49
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