Mathematical Modeling and Validation in Physiology - Applications to the Cardiovascular and Respiratory Systems (Paperback, 2013 ed.)


This volume synthesizes theoretical and practical aspects of both the mathematical and life science viewpoints needed for modeling of the cardiovascular-respiratory system specifically and physiological systems generally. Theoretical points include model design, model complexity and validation in the light of available data, as well as control theory approaches to feedback delay and Kalman filter applications to parameter identification. State of the art approaches using parameter sensitivity are discussed for enhancing model identifiability through joint analysis of model structure and data. Practical examples illustrate model development at various levels of complexity based on given physiological information. The sensitivity-based approaches for examining model identifiability are illustrated by means of specific modeling examples. The themes presented address the current problem of patient-specific model adaptation in the clinical setting, where data is typically limited.

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Product Description

This volume synthesizes theoretical and practical aspects of both the mathematical and life science viewpoints needed for modeling of the cardiovascular-respiratory system specifically and physiological systems generally. Theoretical points include model design, model complexity and validation in the light of available data, as well as control theory approaches to feedback delay and Kalman filter applications to parameter identification. State of the art approaches using parameter sensitivity are discussed for enhancing model identifiability through joint analysis of model structure and data. Practical examples illustrate model development at various levels of complexity based on given physiological information. The sensitivity-based approaches for examining model identifiability are illustrated by means of specific modeling examples. The themes presented address the current problem of patient-specific model adaptation in the clinical setting, where data is typically limited.

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Product Details

General

Imprint

Springer-Verlag

Country of origin

Germany

Series

Lecture Notes in Mathematics, 2064

Release date

December 2012

Availability

Expected to ship within 10 - 15 working days

First published

2013

Editors

, ,

Dimensions

235 x 155 x 19mm (L x W x T)

Format

Paperback

Pages

254

Edition

2013 ed.

ISBN-13

978-3-642-32881-7

Barcode

9783642328817

Categories

LSN

3-642-32881-4



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