Mathematical Modeling and Validation in Physiology

Applications to the Cardiovascular and Respiratory Systems

Nonfiction, Health & Well Being, Medical, Medical Science, Physiology, Science & Nature, Mathematics, Applied, Science
Cover of the book Mathematical Modeling and Validation in Physiology by , Springer Berlin Heidelberg
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9783642328824
Publisher: Springer Berlin Heidelberg Publication: December 14, 2012
Imprint: Springer Language: English
Author:
ISBN: 9783642328824
Publisher: Springer Berlin Heidelberg
Publication: December 14, 2012
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

More books from Springer Berlin Heidelberg

Cover of the book Pflege von alten Menschen by
Cover of the book Wild Crop Relatives: Genomic and Breeding Resources by
Cover of the book Conditionals and Modularity in General Logics by
Cover of the book Staatseigentum by
Cover of the book Dispersion Forces I by
Cover of the book Porous Materials for Carbon Dioxide Capture by
Cover of the book Geborgenheit: Quelle der Stärke by
Cover of the book Wiederholungs- und Vertiefungskurs Strafrecht by
Cover of the book Games Industry Management by
Cover of the book Thymic Development and Selection of T Lymphocytes by
Cover of the book Alltagskreativität by
Cover of the book Dynamics of Knowledge, Corporate Systems and Innovation by
Cover of the book Aphasie by
Cover of the book Injection Molding by
Cover of the book Der Lebensrückblick in Therapie und Beratung by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy