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001 | 978-3-642-32882-4 | ||
003 | DE-He213 | ||
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007 | cr nn 008mamaa | ||
008 | 121214s2013 gw | s |||| 0|eng d | ||
020 |
_a9783642328824 _9978-3-642-32882-4 |
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024 | 7 |
_a10.1007/978-3-642-32882-4 _2doi |
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_aPDE _2bicssc |
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_a570.285 _223 |
245 | 1 | 0 |
_aMathematical Modeling and Validation in Physiology _h[electronic resource] : _bApplications to the Cardiovascular and Respiratory Systems / _cedited by Jerry J. Batzel, Mostafa Bachar, Franz Kappel. |
264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2013. |
|
300 |
_aXX, 254 p. 83 illus., 34 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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490 | 1 |
_aMathematical Biosciences Subseries, _x2524-6771 ; _v2064 |
|
505 | 0 | _a1 Merging Mathematical and Physiological Knowledge: Dimensions and Challenges -- 2 Mathematical Modeling of Physiological Systems -- 3 Parameter Selection Methods in Inverse Problem Formulation.- 4 Application of the Unscented Kalman Filtering to Parameter Estimation -- 5 Integrative and Reductionist Approaches to Modeling of Control of Breathing -- 6 Parameter Identification in a Respiratory Control System Model with Delay -- 7 Experimental Studies of Respiration and Apnea -- 8 Model Validation and Control Issues in the Respiratory System -- 9 Experimental Studies of the Baroreflex -- 10 Development of Patient Specific Cardiovascular Models Predicting Dynamics in Response to Orthostatic Stress Challenges -- 11 Parameter Estimation of a Model for Baroreflex Control of Unstressed Volume. | |
520 | _aThis 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. | ||
650 | 0 | _aHuman physiology. | |
650 | 0 |
_aBiology _xData processing. |
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650 | 1 | 4 |
_aMathematical and Computational Biology. _0http://scigraph.springernature.com/things/product-market-codes/M31000 |
650 | 2 | 4 |
_aHuman Physiology. _0http://scigraph.springernature.com/things/product-market-codes/B13004 |
650 | 2 | 4 |
_aComputer Appl. in Life Sciences. _0http://scigraph.springernature.com/things/product-market-codes/L17004 |
700 | 1 |
_aBatzel, Jerry J. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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700 | 1 |
_aBachar, Mostafa. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
700 | 1 |
_aKappel, Franz. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9783642328817 |
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_iPrinted edition: _z9783642328831 |
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_aMathematical Biosciences Subseries, _x2524-6771 ; _v2064 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-642-32882-4 |
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