| Summary: | 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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