title: A review of personalized blood glucose prediction strategies for T1DM patients.
abstract: This paper presents a methodological review of models for predicting blood glucose (BG) concentration, risks and BG events. The surveyed models are classified into three categories, and they are presented in summary tables containing the most relevant data regarding the experimental setup for fitting and testing each model as well as the input signals and the performance metrics. Each category exhibits trends that are presented and discussed. This document aims to be a compact guide to determine the modeling options that are currently being exploited for personalized BG prediction.
authors.affiliation: Institut d'Informàtica i Aplicacions, Parc Científic i Tecnològic de la Universitat de Girona, 17003, Girona, Spain.
authors.forename: Silvia
authors.initials: S
authors.lastname: Oviedo
authors.affiliation: Institut d'Informàtica i Aplicacions, Universitat de Girona, Campus Montilivi, Edifici P4, 17071, Girona, Spain.
authors.forename: Josep
authors.initials: J
authors.lastname: Vehí
authors.affiliation: Institut d'Informàtica i Aplicacions, Universitat de Girona, Campus Montilivi, Edifici P4, 17071, Girona, Spain.
authors.forename: Remei
authors.initials: R
authors.lastname: Calm
authors.affiliation: Institut d'Informàtica i Aplicacions, Universitat de Girona, Campus Montilivi, Edifici P4, 17071, Girona, Spain.
authors.forename: Joaquim
authors.identifier: 0000-0002-5507-2808
authors.initials: J
authors.lastname: Armengol
mesh_terms: D001786:Blood Glucose / Q000378:metabolism*; D003922:Diabetes Mellitus, Type 1 / Q000097:blood*; D006801:Humans; D007328:Insulin / Q000097:blood
chemical_list: D001786:Blood Glucose; D007328:Insulin
keywords: artificial pancreas; blood glucose prediction; data-driven BG prediction models; hybrid BG prediction models; physiological BG prediction models; predictive models