Cargando…
Sensitivity analysis and inverse uncertainty quantification for the left ventricular passive mechanics
Personalized computational cardiac models are considered to be a unique and powerful tool in modern cardiology, integrating the knowledge of physiology, pathology and fundamental laws of mechanics in one framework. They have the potential to improve risk prediction in cardiac patients and assist in...
Autores principales: | Lazarus, Alan, Dalton, David, Husmeier, Dirk, Gao, Hao |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9132878/ https://www.ncbi.nlm.nih.gov/pubmed/35377030 http://dx.doi.org/10.1007/s10237-022-01571-8 |
Ejemplares similares
-
Bayesian optimisation for efficient parameter inference in a cardiac mechanics model of the left ventricle
por: Borowska, Agnieszka, et al.
Publicado: (2022) -
Markov chain Monte Carlo with Gaussian processes for fast parameter estimation and uncertainty quantification in a 1D fluid‐dynamics model of the pulmonary circulation
por: Paun, L. Mihaela, et al.
Publicado: (2020) -
Large-Scale Inverse Problems and Quantification of Uncertainty
por: Biegler, Lorenz, et al.
Publicado: (2010) -
Fast parameter inference in a biomechanical model of the left ventricle by using statistical emulation
por: Davies, Vinny, et al.
Publicado: (2019) -
Assessing model mismatch and model selection in a Bayesian uncertainty quantification analysis of a fluid-dynamics model of pulmonary blood circulation
por: Paun, L. Mihaela, et al.
Publicado: (2020)