A comparison of Gaussian processes and polynomial chaos emulators in the context of haemodynamic pulse–wave propagation modelling
A comparison of Gaussian processes and polynomial chaos emulators in the context of haemodynamic pulse–wave propagation modelling
Computational modelling of the cardiovascular system is a promising future direction for patient-specific healthcare. However, the computational cost of these simulators is a bottleneck for their practical use in clinic for real-time digital twins. Emulation can overcome this, yet an extensive investigation into cardiovascular emulators is warranted. In this study, we emulate two one-dimensional haemodynamics models of the pulmonary circulation and compare two common emulation strategies: Gaussian processes (GPs) and polynomial chaos expansions (PCEs). We start by reducing the parameter space of the models through global sensitivity analysis, and then compare both emulation strategies using a multivariate, time-series output quantity of interest and a reduced representation using principal component analysis. We compare the emulators in both forward emulation on test data, as well as in their ability to infer parameters in the inverse problem. Our results indicate that GPs slightly outperform PCEs consistently across every comparison, and that a similar performance is obtained for the emulators of the time-dependent output and reduced output.
This article is part of the theme issue ‘Uncertainty quantification for healthcare and biological systems (Part 1)’.
emulation, Gaussian processes, parameter estimation, polynomial chaos expansions, pulmonary pulse-wave propagation modelling, sensitivity analysis
Paun, L. Mihaela
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Colebank, Mitchel J.
c3413ef8-fceb-46f1-8813-5feac4e5beea
Husmeier, Dirk
08a460fd-0240-4354-bf4d-12ae154aa8b7
13 March 2025
Paun, L. Mihaela
1b65f242-287e-4201-b995-ff6be75f070b
Colebank, Mitchel J.
c3413ef8-fceb-46f1-8813-5feac4e5beea
Husmeier, Dirk
08a460fd-0240-4354-bf4d-12ae154aa8b7
Paun, L. Mihaela, Colebank, Mitchel J. and Husmeier, Dirk
(2025)
A comparison of Gaussian processes and polynomial chaos emulators in the context of haemodynamic pulse–wave propagation modelling.
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 383 (2292), [20240222].
(doi:10.1098/rsta.2024.0222).
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Abstract
Computational modelling of the cardiovascular system is a promising future direction for patient-specific healthcare. However, the computational cost of these simulators is a bottleneck for their practical use in clinic for real-time digital twins. Emulation can overcome this, yet an extensive investigation into cardiovascular emulators is warranted. In this study, we emulate two one-dimensional haemodynamics models of the pulmonary circulation and compare two common emulation strategies: Gaussian processes (GPs) and polynomial chaos expansions (PCEs). We start by reducing the parameter space of the models through global sensitivity analysis, and then compare both emulation strategies using a multivariate, time-series output quantity of interest and a reduced representation using principal component analysis. We compare the emulators in both forward emulation on test data, as well as in their ability to infer parameters in the inverse problem. Our results indicate that GPs slightly outperform PCEs consistently across every comparison, and that a similar performance is obtained for the emulators of the time-dependent output and reduced output.
This article is part of the theme issue ‘Uncertainty quantification for healthcare and biological systems (Part 1)’.
Text
paun-et-al-a-comparison-of-gaussian-processes-and-polynomial-chaos-emulators-in-the-context-of-haemodynamic-pulse-wave
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Accepted/In Press date: 8 October 2024
e-pub ahead of print date: 13 March 2025
Published date: 13 March 2025
Keywords:
emulation, Gaussian processes, parameter estimation, polynomial chaos expansions, pulmonary pulse-wave propagation modelling, sensitivity analysis
Identifiers
Local EPrints ID: 502536
URI: http://eprints.soton.ac.uk/id/eprint/502536
ISSN: 1364-503X
PURE UUID: 80dd1bd3-183f-4197-9091-1780a616031f
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Date deposited: 30 Jun 2025 17:43
Last modified: 10 Sep 2025 13:43
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Contributors
Author:
L. Mihaela Paun
Author:
Mitchel J. Colebank
Author:
Dirk Husmeier
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