- Abstract:
-
Computational cardiac models provide important insights into the underlying mechanisms of heart function. Parameter estimation in these models is an ongoing challenge with many existing models being overparameterised. Sensitivity analysis presents a key tool for exploring the parameter identifiability. While existing methods provide insights into the significance of the parameters, they are unable to identify redundant parameters in an efficient manner. We present a new singular value decompo...
Expand abstract - Publisher copy:
- 10.1016/j.future.2011.09.006
-
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- Journal:
- Future Generation Computer Systems
- Volume:
- 29
- Issue:
- 2
- Pages:
- 591-598
- Publication date:
- 2013-02-05
- DOI:
- ISSN:
-
0167-739X
- URN:
-
uuid:3893ee90-bca9-4685-91ed-8729415246b5
- Source identifiers:
-
366825
- Local pid:
- pubs:366825
- Copyright date:
- 2013
Journal article
A local sensitivity analysis method for developing biological models with identifiable parameters: Application to cardiac ionic channel modelling
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