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Bayesian Sensitivity Analysis of a Cardiac Cell Model Using a Gaussian Process Emulator.

Chang ET, Strong M, Clayton RH - PLoS ONE (2015)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Insigneo Institute for in-silico Medicine, University of Sheffield, Sheffield, United Kingdom; Department of Computer Science University of Sheffield, Sheffield, United Kingdom.

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.

No MeSH data available.


Validation of APD90 emulator output against test data output.This plot shows the difference in the mean APD90 predicted by the emulator and APD90 obtained from the simulator for each of the 20 test data. The difference is calibrated as the number of standard deviations, and the red lines indicate ±2 standard deviations.
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pone.0130252.g003: Validation of APD90 emulator output against test data output.This plot shows the difference in the mean APD90 predicted by the emulator and APD90 obtained from the simulator for each of the 20 test data. The difference is calibrated as the number of standard deviations, and the red lines indicate ±2 standard deviations.

Mentions: The evaluation of the APD90 emulator against test data is shown in Fig 3, which shows the difference between the output of the emulator and the output of the simulator for each of the 20 test data. These differences all fall within ± 2 emulator standard deviations, indicating that the emulator is a good fit. The Mahalanobis Distance (MD) for these test data was 28.22, which is within the plausible range given the reference distribution (mean 20 and standard deviation 6.8) [29]. See the Supporting Information (S1 Text) for details of how the MD was calculated. We therefore concluded that the APD90 emulator was a good representation of the simulator.


Bayesian Sensitivity Analysis of a Cardiac Cell Model Using a Gaussian Process Emulator.

Chang ET, Strong M, Clayton RH - PLoS ONE (2015)

Validation of APD90 emulator output against test data output.This plot shows the difference in the mean APD90 predicted by the emulator and APD90 obtained from the simulator for each of the 20 test data. The difference is calibrated as the number of standard deviations, and the red lines indicate ±2 standard deviations.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4482712&req=5

pone.0130252.g003: Validation of APD90 emulator output against test data output.This plot shows the difference in the mean APD90 predicted by the emulator and APD90 obtained from the simulator for each of the 20 test data. The difference is calibrated as the number of standard deviations, and the red lines indicate ±2 standard deviations.
Mentions: The evaluation of the APD90 emulator against test data is shown in Fig 3, which shows the difference between the output of the emulator and the output of the simulator for each of the 20 test data. These differences all fall within ± 2 emulator standard deviations, indicating that the emulator is a good fit. The Mahalanobis Distance (MD) for these test data was 28.22, which is within the plausible range given the reference distribution (mean 20 and standard deviation 6.8) [29]. See the Supporting Information (S1 Text) for details of how the MD was calculated. We therefore concluded that the APD90 emulator was a good representation of the simulator.

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Insigneo Institute for in-silico Medicine, University of Sheffield, Sheffield, United Kingdom; Department of Computer Science University of Sheffield, Sheffield, United Kingdom.

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.

No MeSH data available.