Melis, A. orcid.org/0000-0002-8261-0421, Clayton, R.H. orcid.org/0000-0002-8438-7518 and Marzo, A. orcid.org/0000-0002-6702-7932 (2017) Bayesian sensitivity analysis of a 1D vascular model with Gaussian process emulators. International Journal for Numerical Methods in Biomedical Engineering, 33 (12). e2882. ISSN 2040-7939
Abstract
One-dimensional models of the cardiovascular system can capture the physics of pulse waves, but involve many parameters. Since these may vary among individuals, patient-specific models are difficult to construct. Sensitivity analysis can be used to rank model parameters by their effect on outputs, and to quantify how uncertainty in parameters influences output uncertainty. This type of analysis is often conducted with a Monte Carlo method, where large numbers of model runs are used to assess input-output relations. The aim of this study was to demonstrate the computational efficiency of variance based sensitivity analysis of 1D vascular models using Gaussian process emulators, compared to a standard Monte Carlo approach. The methodology was tested on four vascular networks of increasing complexity to analyse its scalability. The computational time needed to perform the sensitivity analysis with an emulator was reduced by the 99.96% compared to a Monte Carlo approach. Despite the reduced computational time, sensitivity indices obtained using the two approaches were comparable. The scalability study showed that the number of mechanistic simulations needed to train a Gaussian process for sensitivity analysis was of the order math formula, rather than math formula needed for Monte Carlo analysis (where d is the number of parameters in the model). The efficiency of this approach, combined with capacity to estimate the impact of uncertain parameters on model outputs, will enable development of patient-specific models of the vascular system, and has the potential to produce results with clinical relevance.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 The Authors International Journal for Numerical Methods in Biomedical Engineering Published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | 1D vascular model; Gaussian process; emulator; sensitivity analysis; Sobol |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield) |
Funding Information: | Funder Grant number ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL (EPSRC) EP/K037145/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 20 Apr 2017 09:42 |
Last Modified: | 23 Feb 2024 14:28 |
Status: | Published |
Publisher: | Wiley |
Refereed: | Yes |
Identification Number: | 10.1002/cnm.2882 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:115191 |