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Multi-step approach for sensitivity analysis for a unified model of glucose-insulin metabolism

  • Mathematical models of biomedical systems often have a high number of uncertain parameters that are difficult or even impossible to estimate precisely. In order to be able to adequately describe the system, it must be known how large the influence of which factors is on the model behavior and how uncertainties in the parameters affect the model accuracy. Sensitivity analysis (SA) offers a possibility to examine to what extent the variance of the model output can be described by the variability of the input factors. In this paper, a multi-step SA is fulfilled for a unified model of glucose-insulin metabolism that consists of an Elementary Effects Test for screening purposes, a functional principal component analysis for dimensionality reduction of the model output variance and a variance-based approach to determine the sensitivity indices. The concept is tested on several scenarios for type 1 and type 2 diabetic patients, as well as non-diabetics. Results show that parameters are ofMathematical models of biomedical systems often have a high number of uncertain parameters that are difficult or even impossible to estimate precisely. In order to be able to adequately describe the system, it must be known how large the influence of which factors is on the model behavior and how uncertainties in the parameters affect the model accuracy. Sensitivity analysis (SA) offers a possibility to examine to what extent the variance of the model output can be described by the variability of the input factors. In this paper, a multi-step SA is fulfilled for a unified model of glucose-insulin metabolism that consists of an Elementary Effects Test for screening purposes, a functional principal component analysis for dimensionality reduction of the model output variance and a variance-based approach to determine the sensitivity indices. The concept is tested on several scenarios for type 1 and type 2 diabetic patients, as well as non-diabetics. Results show that parameters are of different importance, depending on the type and scenario studied, which should be considered in a further system analysis.show moreshow less

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Metadaten
Author:Christian Tolks, Christoph AmentORCiDGND, Claudia Eberle
URN:urn:nbn:de:bvb:384-opus4-1171244
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/117124
ISSN:2405-8963OPAC
Parent Title (English):IFAC-PapersOnLine
Publisher:Elsevier BV
Type:Article
Language:English
Year of first Publication:2020
Publishing Institution:Universität Augsburg
Release Date:2024/12/02
Volume:53
Issue:2
First Page:16394
Last Page:16399
DOI:https://doi.org/10.1016/j.ifacol.2020.12.680
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Ingenieurinformatik mit Schwerpunkt Regelungstechnik
Nachhaltigkeitsziele
Nachhaltigkeitsziele / Ziel 3 - Gesundheit und Wohlergehen
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 60 Technik / 600 Technik, Technologie
Licence (German):CC-BY-NC-ND 4.0: Creative Commons: Namensnennung - Nicht kommerziell - Keine Bearbeitung (mit Print on Demand)