Artificial intelligence methodologies and their application to diabetes

Rigla Cros, Mercedes; García Sáez, Gema; Pons Pons, Belén y 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/doi.org/10.1177/19322968177104.

Descripción

Título: Artificial intelligence methodologies and their application to diabetes
Autor/es:
  • Rigla Cros, Mercedes
  • García Sáez, Gema
  • Pons Pons, Belén
  • Hernando Pérez, María Elena
Tipo de Documento: Artículo
Título de Revista/Publicación: Journal of diabetes science and technology
Fecha: Mayo 2017
Volumen: 11
Materias:
Palabras Clave Informales: artificial intelligence, decision support, diabetes, machine learning
Escuela: E.T.S.I. Telecomunicación (UPM)
Departamento: Tecnología Fotónica y Bioingeniería
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

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.

Más información

ID de Registro: 49927
Identificador DC: http://oa.upm.es/49927/
Identificador OAI: oai:oa.upm.es:49927
Identificador DOI: doi.org/10.1177/19322968177104
URL Oficial: http://journals.sagepub.com/doi/10.1177/1932296817710475#
Depositado por: Memoria Investigacion
Depositado el: 17 Abr 2018 17:00
Ultima Modificación: 17 Abr 2018 17:00
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