Literature DB >> 27644067

A review of personalized blood glucose prediction strategies for T1DM patients.

Silvia Oviedo1, Josep Vehí2, Remei Calm2, Joaquim Armengol2.   

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.
Copyright © 2016 John Wiley & Sons, Ltd.

Entities:  

Keywords:  artificial pancreas; blood glucose prediction; data-driven BG prediction models; hybrid BG prediction models; physiological BG prediction models; predictive models

Mesh：

Substances：

Year:  2016        PMID： 27644067     DOI： 10.1002/cnm.2833

Source DB:  PubMed          Journal:  Int J Numer Method Biomed Eng        ISSN： 2040-7939            Impact factor:   2.747


  31 in total

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Authors:  Gabriela Voskerician
Journal:  J Mater Sci Mater Med       Date:  2017-01-09       Impact factor: 3.896

2.  Incorporating Unannounced Meals and Exercise in Adaptive Learning of Personalized Models for Multivariable Artificial Pancreas Systems.

Authors:  Iman Hajizadeh; Mudassir Rashid; Kamuran Turksoy; Sediqeh Samadi; Jianyuan Feng; Mert Sevil; Nicole Hobbs; Caterina Lazaro; Zacharie Maloney; Elizabeth Littlejohn; Ali Cinar
Journal:  J Diabetes Sci Technol       Date:  2018-07-31

3.  Hypoglycemia Prevention via Personalized Glucose-Insulin Models Identified in Free-Living Conditions.

Authors:  Chiara Toffanin; Eleonora Maria Aiello; Claudio Cobelli; Lalo Magni
Journal:  J Diabetes Sci Technol       Date:  2019-10-23

4.  Feature-Based Machine Learning Model for Real-Time Hypoglycemia Prediction.

Authors:  Darpit Dave; Daniel J DeSalvo; Balakrishna Haridas; Siripoom McKay; Akhil Shenoy; Chester J Koh; Mark Lawley; Madhav Erraguntla
Journal:  J Diabetes Sci Technol       Date:  2020-06-01

5.  Plasma-Insulin-Cognizant Adaptive Model Predictive Control for Artificial Pancreas Systems.

Authors:  Iman Hajizadeh; Mudassir Rashid; Ali Cinar
Journal:  J Process Control       Date:  2019-04-10       Impact factor: 3.666

6.  Decision Support in Diabetes Care: The Challenge of Supporting Patients in Their Daily Living Using a Mobile Glucose Predictor.

Authors:  Carmen Pérez-Gandía; Gema García-Sáez; David Subías; Agustín Rodríguez-Herrero; Enrique J Gómez; Mercedes Rigla; M Elena Hernando
Journal:  J Diabetes Sci Technol       Date:  2018-03

7.  Data Based Prediction of Blood Glucose Concentrations Using Evolutionary Methods.

Authors:  J Ignacio Hidalgo; J Manuel Colmenar; Gabriel Kronberger; Stephan M Winkler; Oscar Garnica; Juan Lanchares
Journal:  J Med Syst       Date:  2017-08-08       Impact factor: 4.460

8.  Glucose Prediction under Variable-Length Time-Stamped Daily Events: A Seasonal Stochastic Local Modeling Framework.

Authors:  Eslam Montaser; José-Luis Díez; Jorge Bondia
Journal:  Sensors (Basel)       Date:  2021-05-04       Impact factor: 3.576

9.  Using LSTMs to learn physiological models of blood glucose behavior.

Authors:  Sadegh Mirshekarian; Razvan Bunescu; Cindy Marling; Frank Schwartz
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2017-07

10.  Blood Glucose Level Forecasting on Type-1-Diabetes Subjects during Physical Activity: A Comparative Analysis of Different Learning Techniques.

Authors:  Benedetta De Paoli; Federico D'Antoni; Mario Merone; Silvia Pieralice; Vincenzo Piemonte; Paolo Pozzilli
Journal:  Bioengineering (Basel)       Date:  2021-05-26
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