4 papers
Uncertainty-aware classification and triage of structural heart disease using electrocardiography and echocardiography metrics
Mitchel J. Colebank
Machine learning methods provide a methodological innovation that can help screen for cardiovascular disease through noninvasive and readily available measurement modalities. Recen…
Mathematical simulations of pediatric hemodynamics in isolated ventricular septal defect
Mitchel J. Colebank, Alfonso Limon, Anthony Chang +3
Computer modeling of the cardiovascular system has potential to revolutionize personalized medical care. This is especially promising for congenital heart defects, such as ventricu…
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…
Assessing parameter identifiability of a hemodynamics PDE model using spectral surrogates and dimension reduction
Mitchel J. Colebank
Computational inverse problems for biomedical simulators suffer from limited data and relatively high parameter dimensionality. This often requires sensitivity analysis, where para…