Data-based identification of prediction models for glucose

J. Manuel Velasco, Stephan Winkler, J. Ignacio Hidalgo, Oscar Garnica, Juan Lanchares, J. Manuel Colmenar, Esther Maqueda, Marta Botella, Jose Antonio Rubio

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

2 Citations (Scopus)

Abstract

Diabetes mellitus is a disease that affects to hundreds of million of people worldwide. Maintaining a good control of the disease is critical to avoid severe long-term complications. One of the main problems that arise in the (semi) automatic control of diabetes, is to get a model explaining how glycemia (glucose levels in blood) varies with insulin, food intakes and other factors, fitting the characteristics of each individual or patient. In this paper we compare genetic programming techniques with a set of clsssical identification techniques: classical simple exponential smoothing, Holt's smoothing (linear, exponential and damped), classical Holt and Winters methods and auto regressive integrated moving average modelling. We consider predictions horizons of 30, 60, 90 and 120 minutes. Experimental results shows the difficulty of predicting glucose values for more than 60 minutes and the necessity of adapt GP techniques for those dynamic enviroments.

Original languageEnglish
Title of host publicationGECCO 2015 - Companion Publication of the 2015 Genetic and Evolutionary Computation Conference
EditorsSara Silva
PublisherAssociation for Computing Machinery, Inc
Pages1327-1334
Number of pages8
ISBN (Electronic)9781450334884
DOIs
Publication statusPublished - 11 Jul 2015
Event17th Genetic and Evolutionary Computation Conference, GECCO 2015 - Madrid, Spain
Duration: 11 Jul 201515 Jul 2015

Publication series

NameGECCO 2015 - Companion Publication of the 2015 Genetic and Evolutionary Computation Conference

Conference

Conference17th Genetic and Evolutionary Computation Conference, GECCO 2015
CountrySpain
CityMadrid
Period11.07.201515.07.2015

Keywords

  • Diabetes
  • Genetic programming
  • Modeling

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