Cargando…
Bayesian Sensitivity Analysis of a Cardiac Cell Model Using a Gaussian Process Emulator
Models of electrical activity in cardiac cells have become important research tools as they can provide a quantitative description of detailed and integrative physiology. However, cardiac cell models have many parameters, and how uncertainties in these parameters affect the model output is difficult...
Autores principales: | Chang, Eugene T Y, Strong, Mark, Clayton, Richard H |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4482712/ https://www.ncbi.nlm.nih.gov/pubmed/26114610 http://dx.doi.org/10.1371/journal.pone.0130252 |
Ejemplares similares
-
Correction: Bayesian Sensitivity Analysis of a Cardiac Cell Model Using a Gaussian Process Emulator
por: Chang, Eugene T. Y., et al.
Publicado: (2015) -
Sensitivity and Uncertainty Analysis of Two Human Atrial Cardiac Cell Models Using Gaussian Process Emulators
por: Coveney, Sam, et al.
Publicado: (2020) -
Bayesian(3) Active Learning for the Gaussian Process Emulator Using Information Theory
por: Oladyshkin, Sergey, et al.
Publicado: (2020) -
GpABC: a Julia package for approximate Bayesian computation with Gaussian process emulation
por: Tankhilevich, Evgeny, et al.
Publicado: (2020) -
Bayesian Calibration of Electrophysiology Models Using Restitution Curve Emulators
por: Coveney, Sam, et al.
Publicado: (2021)