Personalised parameter estimation of the cardiovascular system: Leveraging data assimilation and sensitivity analysis

Saxton, H. orcid.org/0000-0001-7433-6154, Schenkel, T., Halliday, I. et al. (1 more author) (2023) Personalised parameter estimation of the cardiovascular system: Leveraging data assimilation and sensitivity analysis. Journal of Computational Science, 74. 102158. ISSN 1877-7503

Abstract

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Item Type: Article
Authors/Creators:
Copyright, Publisher and Additional Information:

© 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Keywords: Data assimilation; Dynamical systems; Uncertainty quantification; Parameter estimation
Dates:
  • Published: December 2023
  • Published (online): 28 October 2023
  • Accepted: 9 October 2023
  • Submitted: 30 June 2023
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 06 Dec 2023 12:54
Last Modified: 06 Dec 2023 12:54
Status: Published
Publisher: Elsevier BV
Refereed: Yes
Identification Number: 10.1016/j.jocs.2023.102158
Open Archives Initiative ID (OAI ID):

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