title: Sensitivity analysis of cardiac electrophysiological models using polynomial chaos.
abstract: Mathematical models of biophysical phenomena have proven useful in the reconstruction of experimental data and prediction of biological behavior. By quantifying the sensitivity of a model to certain parameters, one can place an appropriate amount of emphasis in the accuracy with which those parameters are determined. In addition, investigation of stochastic parameters can lead to a greater understanding of the behavior captured by the model. This can lead to possible model reductions, or point out shortcomings to be addressed. We present polynomial chaos as a computationally efficient alternative to Monte Carlo for assessing the impact of stochastically distributed parameters on the model predictions of several cardiac electrophysiological models.
authors.affiliation: School of Computing and Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA.
authors.forename: Sarah
authors.initials: S
authors.lastname: Geneser
authors.forename: Robert
authors.initials: R
authors.lastname: Kirby
authors.forename: Frank
authors.initials: F
authors.lastname: Sachse