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| Genre/Form: | Electronic books |
|---|---|
| Additional Physical Format: | Print version: Cobelli, Claudio. Introduction to Modeling in Physiology and Medicine. San Diego : Elsevier Science & Technology, ©2019 |
| Material Type: | Document, Internet resource |
| Document Type: | Internet Resource, Computer File |
| All Authors / Contributors: |
Claudio Cobelli; Ewart Carson |
| ISBN: | 0128158050 9780128158050 |
| OCLC Number: | 1111961795 |
| Notes: | 5.4.1.4 The whole-organ model |
| Description: | 1 online resource (386 pages) |
| Contents: | Front Cover; Introduction to Modeling in Physiology and Medicine; Copyright Page; Contents; Preface to the second edition; Preface to the first edition; 1 Introduction; 1.1 Introduction; 1.2 The book in context; 1.3 The major ingredients; 1.4 Readership and prerequisites; 1.5 Organization of the book; 2 Physiological complexity and the need for models; 2.1 Introduction; 2.2 Complexity; 2.3 System dynamics; 2.3.1 First-order linear time-invariant systems; 2.3.2 The dynamic behavior of first-order linear time-invariant systems-solution by integration 2.3.3 The classical solution for a first-order system2.3.4 General case of a first-order linear system; 2.4 Feedback; 2.4.1 Negative feedback; 2.4.2 Positive feedback; 2.4.3 Inherent feedback; 2.4.4 Combining negative and positive feedback; 2.4.5 Derivative and integral feedback; 2.4.6 Effects of feedback on the complexity of system dynamics; 2.5 Control in physiological systems; 2.5.1 General features; 2.5.2 Enzymes; 2.5.3 Hormones; 2.6 Hierarchy; 2.7 Redundancy; 2.8 Function and behavior and their measurement; 2.9 Challenges to understanding; 2.10 Exercises and assignment questions 3 Models and the modeling process3.1 Introduction; 3.2 What is a model?; 3.3 Why model? The purpose of modeling; 3.4 How do we model? The modeling process; 3.5 Model formulation; 3.6 Model identification; 3.7 Model validation; 3.8 Model simulation; 3.9 Summary; 3.10 Exercises and assignment questions; 4 Modeling the data; 4.1 Introduction; 4.2 The basis of data modeling; 4.3 The why and when of data models; 4.4 Approaches to data modeling; 4.5 Modeling a single variable occurring spontaneously; 4.5.1 Temperature; 4.5.2 Urine potassium; 4.5.3 Gastrointestinal rhythms 4.5.4 Hormonal time series4.6 Modeling a single variable in response to a perturbation; 4.6.1 Glucose home monitoring data; 4.6.2 Response to drug therapy-prediction of bronchodilator response; 4.7 Two variables causally related; 4.7.1 Hormone/hormone and substrate/hormone series; 4.7.2 Urine sodium response to water loading; 4.8 Input/output modeling for control; 4.8.1 Pupil control; 4.8.2 Control of blood glucose by insulin; 4.8.3 Control of blood pressure by sodium nitroprusside; 4.9 Input/output modeling: impulse response and deconvolution; 4.9.1 Impulse response estimation 4.9.2 The convolution integral4.9.3 Reconstructing the input; 4.10 Summary; 4.11 Exercises and assignment questions; 5 Modeling the system; 5.1 Introduction; 5.2 Static models; 5.3 Linear modeling; 5.3.1 The Windkessel circulatory model; 5.3.2 Elimination from a single compartment; 5.3.3 Gas exchange; 5.3.4 The dynamics of a swinging limb; 5.3.5 A model of glucose regulation; 5.4 Distributed modeling; 5.4.1 Blood-tissue exchange; 5.4.1.1 The single-capillary model; 5.4.1.2 The capillary-interstitial fluid model; 5.4.1.3 The capillary-interstitial fluid-cell model |
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