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• W788330839 startingPage "e0130252" @default.
• W788330839 abstract "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 to assess without undertaking large numbers of model runs. In this study we show that a surrogate statistical model of a cardiac cell model (the Luo-Rudy 1991 model) can be built using Gaussian process (GP) emulators. Using this approach we examined how eight outputs describing the action potential shape and action potential duration restitution depend on six inputs, which we selected to be the maximum conductances in the Luo-Rudy 1991 model. We found that the GP emulators could be fitted to a small number of model runs, and behaved as would be expected based on the underlying physiology that the model represents. We have shown that an emulator approach is a powerful tool for uncertainty and sensitivity analysis in cardiac cell models." @default.
• W788330839 created "2016-06-24" @default.
• W788330839 creator A5032200106 @default.
• W788330839 creator A5058791528 @default.
• W788330839 creator A5061404499 @default.
• W788330839 date "2015-06-26" @default.
• W788330839 modified "2023-10-14" @default.
• W788330839 title "Bayesian Sensitivity Analysis of a Cardiac Cell Model Using a Gaussian Process Emulator" @default.
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• W788330839 doi "https://doi.org/10.1371/journal.pone.0130252" @default.
• W788330839 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4482712" @default.
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• W788330839 hasPublicationYear "2015" @default.
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