Markov Chain Monte Carlo with Gaussian Process Emulation for a 1D Hemodynamics Model of CTEPH

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autori principali: Kachabi, Amirreza, Colebank, Mitchel J., Correa, Sofia Altieri, Chesler, Naomi C.
Natura: Preprint
Pubblicazione: 2024
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866916279347052544
author Kachabi, Amirreza
Colebank, Mitchel J.
Correa, Sofia Altieri
Chesler, Naomi C.
author_facet Kachabi, Amirreza
Colebank, Mitchel J.
Correa, Sofia Altieri
Chesler, Naomi C.
contents Microvascular disease is a contributor to persistent pulmonary hypertension in those with chronic thromboembolic pulmonary hypertension (CTEPH). The heterogenous nature of the micro and macrovascular defects motivates the use of personalized computational models, which can predict flow dynamics within multiple generations of the arterial tree and into the microvasculature. Our study uses computational hemodynamics models and Gaussian processes for rapid, subject-specific calibration using retrospective data from a large animal model of CTEPH. Our subject-specific predictions shed light on microvascular dysfunction and arterial wall shear stress changes in CTEPH.
format Preprint
id arxiv_https___arxiv_org_abs_2406_01599
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Markov Chain Monte Carlo with Gaussian Process Emulation for a 1D Hemodynamics Model of CTEPH
Kachabi, Amirreza
Colebank, Mitchel J.
Correa, Sofia Altieri
Chesler, Naomi C.
Quantitative Methods
Computational Engineering, Finance, and Science
Machine Learning
Data Analysis, Statistics and Probability
Applications
Microvascular disease is a contributor to persistent pulmonary hypertension in those with chronic thromboembolic pulmonary hypertension (CTEPH). The heterogenous nature of the micro and macrovascular defects motivates the use of personalized computational models, which can predict flow dynamics within multiple generations of the arterial tree and into the microvasculature. Our study uses computational hemodynamics models and Gaussian processes for rapid, subject-specific calibration using retrospective data from a large animal model of CTEPH. Our subject-specific predictions shed light on microvascular dysfunction and arterial wall shear stress changes in CTEPH.
title Markov Chain Monte Carlo with Gaussian Process Emulation for a 1D Hemodynamics Model of CTEPH
topic Quantitative Methods
Computational Engineering, Finance, and Science
Machine Learning
Data Analysis, Statistics and Probability
Applications
url https://arxiv.org/abs/2406.01599