Sensitivity analysis of cardiac electrophysiological models using polynomial chaos

被引：5

作者：

Geneser, Sarah E. ^{[1
]}

Kirby, Robert M. ^{[1
]}

Sachse, Frank B. ^{[1
]}

机构：

[1] Univ Utah, Sch Comp, Salt Lake City, UT 84112 USA

来源：

2005 27TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-7 | 2005年

关键词：

polynomial chaos; stochastic processes; sensitivity quantification; biological computational modeling; cardiac electrophysiology;

D O I：

10.1109/IEMBS.2005.1615349

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

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.

引用

页码：4042 / 4045

页数：4

共 12 条

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