8 citations · 13 across the 4 of their papers we have counts for
4 papers
A Bayesian Framework for Uncertainty-Aware Estimation of Main Pulmonary Artery Velocity Profiles from Phase-Contrast MRI
Amirreza Kachabi, Naomi C. Chesler
Computational cardiovascular flow models are highly sensitive to prescribed inlet velocity profiles. While imaging-derived velocity fields provide physiologically realistic informa…
Bayesian Parameter Inference and Uncertainty Quantification for a Computational Pulmonary Hemodynamics Model Using Gaussian Processes
Amirreza Kachabi, Sofia Altieri Correa, Naomi C. Chesler +1
Subject-specific modeling is a powerful tool in cardiovascular research, providing insights beyond the reach of current clinical diagnostics. Limitations in available clinical data…
Markov Chain Monte Carlo with Gaussian Process Emulation for a 1D Hemodynamics Model of CTEPH
Amirreza Kachabi, Mitchel J. Colebank, Sofia Altieri Correa +1
Microvascular disease is a contributor to persistent pulmonary hypertension in those with chronic thromboembolic pulmonary hypertension (CTEPH). The heterogenous nature of the micr…
Efficient Uncertainty Quantification in a Multiscale Model of Pulmonary Arterial and Venous Hemodynamics
Mitchel J. Colebank, Naomi C. Chesler
Computational hemodynamics models are becoming increasingly useful in the management and prognosis of complex, multiscale pathologies, including those attributed to the development…