Introduction to Modeling in Physiology and Medicine

This unified physiological modeling textbook is for students taking modeling and physiological courses in biomedical engineering and the biological and life sciences. It provides a complete introduction to the foundations, theory and practice of modeling and simulation in medicine, bioscience and engineering, and for clinical applications.Introduction to Modeling in Physiology and Medicine, Second Edition develops a clear understanding of the fundamental principles of good modeling methodology. Readers are shown how to create valid mathematical models that are fit for a range of purposes, supported throughout by detailed explanation, extensive case studies, examples and applications. New to this Edition: Clearer guidance is provided on the mathematical prerequisites needed to achieve the maximum benefit from the material to be found, particularly in the later chaptersGreater detail regarding basic approaches to modeling is provided, particularly in the Non-linear and Stochastic Modeling sections in Chapter 5The range of case study material has been substantially extended, with examples drawn from recent research experienceKey examples include: a cellular model of insulin secretion and its extension to the whole-body level; a model of insulin action during a meal/oral glucose tolerance test; a large-scale simulation model of type 1 diabetes and its use in in silico clinical trials and drug trials Covers the underlying principles of good quantitative modeling methodology, with applied biomedical engineering and bioscience examples to ensure relevance to students, current research and clinical practiceKey topics include: modeling data, modeling systems, linear and non-linear systems; model identification; parametric and non-parametric models; and model validationClear, step-by-step working plus examples and extensive case studies relate concepts to real world applications; end of chapter exercises and assignments reinforce learning INDICE: 1. Introduction 2. Physiological Complexity and the Need for Models 3. Models and the Modeling Process 4. Modeling the Data 5. Modeling the System 6. Model Identification 7. Parametric Models - The Identifiability Problem 8. Parametric Models - The Estimation Problem 9. Non-parametric Models - Signal Estimation 10. Model Validation 11. Case Studies

• ISBN: 978-0-12-815756-5
• Editorial: Academic Press
• Encuadernacion: Rústica
• Páginas: 350
• Fecha Publicación: 01/08/2019
• Nº Volúmenes: 1
• Idioma: Inglés