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Titre : Biomedical Information Technology Type de document : texte imprimé Auteurs : David Dagan Feng, Auteur Editeur : Amsterdam,Boston,Heidelberg... : Elsevier Academic Press Année de publication : 2008 Collection : Academic Press Series in Biomedical Engineering Importance : 525 p. Présentation : couv. ill. en coul., ill. Format : 28,5 cm ISBN/ISSN/EAN : 978-0-12-373583-6 Langues : Anglais (eng) Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-09 Informatique biomédicale Résumé : The enormous growth in the field of biotechnology necessitates the utilization of information technology for the management, flow and organization of data. The field continues to evolve with the development of new applications to fit the needs of the biomedicine. From molecular imaging to healthcare knowledge management, the storage, access and analysis of data contributes significantly to biomedical research and practice.
All biomedical professionals can benefit from a greater understanding of how data can be efficiently managed and utilized through data compression, modelling, processing, registration, visualization, communication, and large-scale biological computing. In addition Biomedical Information Technology contains practical integrated clinical applications for disease detection, diagnosis, surgery, therapy, and biomedical knowledge discovery, including the latest advances in the field, such as ubiquitous M-Health systems and molecular imaging applications.
The world's most recognized authorities give their "best practices" ready for implementation
Provides professionals with the most up to date and mission critical tools to evaluate the latest advances in the field and current integrated clinical applications
Gives new staff the technological fundamentals and updates experienced professionals with the latest practical integrated clinical applicationsNote de contenu : Contents
Section I: Technological Fundamentals
Chapter 1: Medical Imaging
Chapter 2: Electronic Medical Records
Chapter 3: Image Data Compression and Storage
Chapter 4: Content-Based Medical Image Retrieval
Chapter 5: Data Modeling and Simulation
Chapter 6: Techniques for Parametric Imaging
Chapter 7: Data Processing and Analysis
Chapter 8: Data Registration and Fusion
Chapter 9: Data Visualization and Display
Chapter 10: Data Communication and Network Infrastructure
Chapter 11: Data Security and Protection for Medical Images
Chapter 12: Biologic Computing
SECTION II: Integrated applications
Chapter 13: PACS and Medical Imaging Informatics for Filmless hospitals
Chapter 14: KMeX: A Knowledge-Based Digital Library for Retrieving scenario-specific Medical text documents
Chapter 15: Integrated Multimedia Patient Record Systems
Chapter 16: Computer-Aided Diagnosis
Chapter 17: Clinical Decision Support Systems
Chapter 18: Medical Robotics and Computer-Integrated Interventional medicine
Chapter 19: Functional Techniques for Brain Magnetic Resonance imaging
Chapter 20: Molecular Imaging in Cancer
Chapter 21: Molecular Imaging in Biology and Pharmacology
Chapter 22: From Telemedicine to Ubiquitous M-Health: The E-health systems
Chapter 23: Multimedia for Future Health-Smart Medical Home
Index
Biomedical Information Technology [texte imprimé] / David Dagan Feng, Auteur . - Amsterdam,Boston,Heidelberg... : Elsevier Academic Press, 2008 . - 525 p. : couv. ill. en coul., ill. ; 28,5 cm. - (Academic Press Series in Biomedical Engineering) .
ISBN : 978-0-12-373583-6
Langues : Anglais (eng)
Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-09 Informatique biomédicale Résumé : The enormous growth in the field of biotechnology necessitates the utilization of information technology for the management, flow and organization of data. The field continues to evolve with the development of new applications to fit the needs of the biomedicine. From molecular imaging to healthcare knowledge management, the storage, access and analysis of data contributes significantly to biomedical research and practice.
All biomedical professionals can benefit from a greater understanding of how data can be efficiently managed and utilized through data compression, modelling, processing, registration, visualization, communication, and large-scale biological computing. In addition Biomedical Information Technology contains practical integrated clinical applications for disease detection, diagnosis, surgery, therapy, and biomedical knowledge discovery, including the latest advances in the field, such as ubiquitous M-Health systems and molecular imaging applications.
The world's most recognized authorities give their "best practices" ready for implementation
Provides professionals with the most up to date and mission critical tools to evaluate the latest advances in the field and current integrated clinical applications
Gives new staff the technological fundamentals and updates experienced professionals with the latest practical integrated clinical applicationsNote de contenu : Contents
Section I: Technological Fundamentals
Chapter 1: Medical Imaging
Chapter 2: Electronic Medical Records
Chapter 3: Image Data Compression and Storage
Chapter 4: Content-Based Medical Image Retrieval
Chapter 5: Data Modeling and Simulation
Chapter 6: Techniques for Parametric Imaging
Chapter 7: Data Processing and Analysis
Chapter 8: Data Registration and Fusion
Chapter 9: Data Visualization and Display
Chapter 10: Data Communication and Network Infrastructure
Chapter 11: Data Security and Protection for Medical Images
Chapter 12: Biologic Computing
SECTION II: Integrated applications
Chapter 13: PACS and Medical Imaging Informatics for Filmless hospitals
Chapter 14: KMeX: A Knowledge-Based Digital Library for Retrieving scenario-specific Medical text documents
Chapter 15: Integrated Multimedia Patient Record Systems
Chapter 16: Computer-Aided Diagnosis
Chapter 17: Clinical Decision Support Systems
Chapter 18: Medical Robotics and Computer-Integrated Interventional medicine
Chapter 19: Functional Techniques for Brain Magnetic Resonance imaging
Chapter 20: Molecular Imaging in Cancer
Chapter 21: Molecular Imaging in Biology and Pharmacology
Chapter 22: From Telemedicine to Ubiquitous M-Health: The E-health systems
Chapter 23: Multimedia for Future Health-Smart Medical Home
Index
Exemplaires(2)
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Titre : Introduction to Biomedical Engineering Type de document : texte imprimé Auteurs : John D. Enderle, Auteur ; Joseph D. Bronzino, Auteur Mention d'édition : 3rd. ed. Editeur : Amsterdam,Boston,Heidelberg... : Elsevier Academic Press Année de publication : 2012 Collection : Academic Press Series in Biomedical Engineering Importance : 1253 p. Présentation : couv. ill. en coul., ill. Format : 24,1 cm. ISBN/ISSN/EAN : 978-0-12-374979-6 Langues : Anglais (eng) Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-01 Génie biomédical général Résumé : Introduction to Biomedical Engineering is a comprehensive survey text for biomedical engineering courses. It is the most widely adopted text across the BME course spectrum, valued by instructors and students alike for its authority, clarity and encyclopedic coverage in a single volume. Biomedical engineers need to understand the wide range of topics that are covered in this text, including basic mathematical modeling; anatomy and physiology; electrical engineering, signal processing and instrumentation; biomechanics; biomaterials science and tissue engineering; and medical and engineering ethics. Enderle and Bronzino tackle these core topics at a level appropriate for senior undergraduate students and graduate students who are majoring in BME, or studying it as a combined course with a related engineering, biology or life science, or medical/pre-medical course. * NEW: Each chapter in the 3rd Edition is revised and updated, with new chapters and materials on compartmental analysis, biochemical engineering, transport phenomena, physiological modeling and tissue engineering. Chapters on peripheral topics have been removed and made avaialblw online, including optics and computational cell biology. * NEW: many new worked examples within chapters * NEW: more end of chapter exercises, homework problems Note de contenu : Contents
Chapter 1: Biomedical Engineering: A Historical Perspective
Chapter 2: Moral and Ethical Issues
Chapter 3: Anatomy and Physiology
Chapter 4: Biomechanics
Chapter 5: Biomaterials
Chapter 6: Tissue Engineering
Chapter 7: Compartmental Modeling
Chapter 8: Biochemical Reactions and Enzyme Kinetics
Chapter 9: Bioinstrumentation
Chapter 10: Biomedical Sensors
Chapter 11: Biosignal Processing
Chapter 12: Bioelectric Phenomena
Chapter 13: Physiological Modeling
Chapter 14: Biomedical Transport Processes
Chapter 15: Radiation Imaging
Chapter 16: Medical Imaging
Chapter 17: Biomedical Optics and Lasers
Appendix
A.1. Matlab
A.2. Solving differential equations using Matlab
A.3. Block diagrams and SIMULINK
A.4. Simulink
Index
Introduction to Biomedical Engineering [texte imprimé] / John D. Enderle, Auteur ; Joseph D. Bronzino, Auteur . - 3rd. ed. . - Amsterdam,Boston,Heidelberg... : Elsevier Academic Press, 2012 . - 1253 p. : couv. ill. en coul., ill. ; 24,1 cm.. - (Academic Press Series in Biomedical Engineering) .
ISBN : 978-0-12-374979-6
Langues : Anglais (eng)
Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-01 Génie biomédical général Résumé : Introduction to Biomedical Engineering is a comprehensive survey text for biomedical engineering courses. It is the most widely adopted text across the BME course spectrum, valued by instructors and students alike for its authority, clarity and encyclopedic coverage in a single volume. Biomedical engineers need to understand the wide range of topics that are covered in this text, including basic mathematical modeling; anatomy and physiology; electrical engineering, signal processing and instrumentation; biomechanics; biomaterials science and tissue engineering; and medical and engineering ethics. Enderle and Bronzino tackle these core topics at a level appropriate for senior undergraduate students and graduate students who are majoring in BME, or studying it as a combined course with a related engineering, biology or life science, or medical/pre-medical course. * NEW: Each chapter in the 3rd Edition is revised and updated, with new chapters and materials on compartmental analysis, biochemical engineering, transport phenomena, physiological modeling and tissue engineering. Chapters on peripheral topics have been removed and made avaialblw online, including optics and computational cell biology. * NEW: many new worked examples within chapters * NEW: more end of chapter exercises, homework problems Note de contenu : Contents
Chapter 1: Biomedical Engineering: A Historical Perspective
Chapter 2: Moral and Ethical Issues
Chapter 3: Anatomy and Physiology
Chapter 4: Biomechanics
Chapter 5: Biomaterials
Chapter 6: Tissue Engineering
Chapter 7: Compartmental Modeling
Chapter 8: Biochemical Reactions and Enzyme Kinetics
Chapter 9: Bioinstrumentation
Chapter 10: Biomedical Sensors
Chapter 11: Biosignal Processing
Chapter 12: Bioelectric Phenomena
Chapter 13: Physiological Modeling
Chapter 14: Biomedical Transport Processes
Chapter 15: Radiation Imaging
Chapter 16: Medical Imaging
Chapter 17: Biomedical Optics and Lasers
Appendix
A.1. Matlab
A.2. Solving differential equations using Matlab
A.3. Block diagrams and SIMULINK
A.4. Simulink
Index
Exemplaires(4)
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Titre : Introduction to Modeling in Physiology and MedicineC Type de document : texte imprimé Auteurs : Claudio Cobelli, Auteur ; Ewart Carson, Auteur Editeur : Amsterdam,Boston,Heidelberg... : Elsevier Academic Press Année de publication : 2008 Collection : Academic Press Series in Biomedical Engineering Importance : 324 p. Présentation : couv. ill. en coul., ill. Format : 24,8 cm. ISBN/ISSN/EAN : 978-0-12-160240-6 Langues : Anglais (eng) Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-04 Modélisation des systèmes physiologiques Résumé : This unified modeling textbook for students of biomedical engineering provides a complete course text on the foundations, theory and practice of modeling and simulation in physiology and medicine. It is dedicated to the needs of biomedical engineering and clinical students, supported by applied BME applications and examples.
• Developed for biomedical engineering and related courses: speaks to BME students at a level and in a language appropriate to their needs, with an interdisciplinary clinical/engineering approach, quantitative basis, and many applied examples to enhance learning
• Delivers a quantitative approach to modeling and also covers simulation: the perfect foundation text for studies across BME and medicine
• Extensive case studies and engineering applications from BME, plus end-of-chapter exercises and a separate Instructor’s manualNote de contenu : CONTENTS
CHAPTER 1 INTRODUCTION
CHAPTER 2 PHYSIOLOGICAL COMPLEXITY AND THE NEED FOR MODELS
2.2 Complexity
2.3 Feedback
2.4 Control in Physiological Systems
2.5 Hierarchy
2.6 Redundancy
2.7 Function and Behavior and their Measurement
2.8 Challenges to Understanding
CHAPTER 3 MODELS AND THE MODELING PROCESS
3.5 Model Formulation
3.6 Model Identification
3.7 Model Validation
3.8 Model Simulation
CHAPTER 4 MODELING THE DATA
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
4.6 Modeling a Single Variable in Response to a Perturbation
4.7 Two Variables Causally Related
4.8 Input/output Modeling for Control
4.9 Input/output Modeling: Impulse Response and Deconvolution
CHAPTER 5 MODELING THE SYSTEM
5.2 Static Models
5.3 Linear Modeling
5.4 Distributed Modeling
5.5 Nonlinear Modeling
5.6 Time-varying Modeling
5.7 Stochastic Modeling
CHAPTER 6 MODEL IDENTIFICATION
6.2 Data for Identification
6.3 Errors
6.4 The Way Forward
CHAPTER 7 PARAMETRIC MODELING – THE IDENTIFIABILITY PROBLEM
7.4 Linear Models: The Transfer Function Method
7.5 Nonlinear Models: The Taylor Series Expansion Method
7.6 Qualitative Experimental Design
CHAPTER 8 PARAMETRIC MODELS – THE ESTIMATION PROBLEM
8.2 Linear and Nonlinear Parameters
8.3 Regression: Basic Concepts
8.4 Linear Regression
8.5 Nonlinear Regression
8.6 Tests for Model Order
8.7 Maximum Likelihood Estimation
8.8 Bayesian Estimation
8.9 Optimal Experimental Design
CHAPTER 9 NON-PARAMETRIC MODELS – SIGNAL ESTIMATION
9.2 Why is Deconvolution Important?
9.3 The Problem
9.4 Difficulty of the Deconvolution Problem
9.5 The Regularization Method
CHAPTER 10 MODEL VALIDATION
10.3 Validation Strategies
10.4 Good Practice in Good Modeling
CHAPTER 11 CASE STUDIES
11.1 Case Study 1: A Sum of Exponentials Tracer Disappearance Model
11.2 Case Study 2: Blood Flow Modeling
11.3 Case Study 3: Cerebral Glucose Modeling
11.4 Case Study 4: Models of the Ligand-Receptor System
11.5 Case Study 5: A Simulation Model of the Glucose-Insulin System
11.5.1 Model Formulation
11.5.2 Results
11.6 Case Study 6: A Model of Insulin Control
11.7 Case Study 7: Illustrations of Bayesian Estimation
INDEXIntroduction to Modeling in Physiology and MedicineC [texte imprimé] / Claudio Cobelli, Auteur ; Ewart Carson, Auteur . - Amsterdam,Boston,Heidelberg... : Elsevier Academic Press, 2008 . - 324 p. : couv. ill. en coul., ill. ; 24,8 cm.. - (Academic Press Series in Biomedical Engineering) .
ISBN : 978-0-12-160240-6
Langues : Anglais (eng)
Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-04 Modélisation des systèmes physiologiques Résumé : This unified modeling textbook for students of biomedical engineering provides a complete course text on the foundations, theory and practice of modeling and simulation in physiology and medicine. It is dedicated to the needs of biomedical engineering and clinical students, supported by applied BME applications and examples.
• Developed for biomedical engineering and related courses: speaks to BME students at a level and in a language appropriate to their needs, with an interdisciplinary clinical/engineering approach, quantitative basis, and many applied examples to enhance learning
• Delivers a quantitative approach to modeling and also covers simulation: the perfect foundation text for studies across BME and medicine
• Extensive case studies and engineering applications from BME, plus end-of-chapter exercises and a separate Instructor’s manualNote de contenu : CONTENTS
CHAPTER 1 INTRODUCTION
CHAPTER 2 PHYSIOLOGICAL COMPLEXITY AND THE NEED FOR MODELS
2.2 Complexity
2.3 Feedback
2.4 Control in Physiological Systems
2.5 Hierarchy
2.6 Redundancy
2.7 Function and Behavior and their Measurement
2.8 Challenges to Understanding
CHAPTER 3 MODELS AND THE MODELING PROCESS
3.5 Model Formulation
3.6 Model Identification
3.7 Model Validation
3.8 Model Simulation
CHAPTER 4 MODELING THE DATA
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
4.6 Modeling a Single Variable in Response to a Perturbation
4.7 Two Variables Causally Related
4.8 Input/output Modeling for Control
4.9 Input/output Modeling: Impulse Response and Deconvolution
CHAPTER 5 MODELING THE SYSTEM
5.2 Static Models
5.3 Linear Modeling
5.4 Distributed Modeling
5.5 Nonlinear Modeling
5.6 Time-varying Modeling
5.7 Stochastic Modeling
CHAPTER 6 MODEL IDENTIFICATION
6.2 Data for Identification
6.3 Errors
6.4 The Way Forward
CHAPTER 7 PARAMETRIC MODELING – THE IDENTIFIABILITY PROBLEM
7.4 Linear Models: The Transfer Function Method
7.5 Nonlinear Models: The Taylor Series Expansion Method
7.6 Qualitative Experimental Design
CHAPTER 8 PARAMETRIC MODELS – THE ESTIMATION PROBLEM
8.2 Linear and Nonlinear Parameters
8.3 Regression: Basic Concepts
8.4 Linear Regression
8.5 Nonlinear Regression
8.6 Tests for Model Order
8.7 Maximum Likelihood Estimation
8.8 Bayesian Estimation
8.9 Optimal Experimental Design
CHAPTER 9 NON-PARAMETRIC MODELS – SIGNAL ESTIMATION
9.2 Why is Deconvolution Important?
9.3 The Problem
9.4 Difficulty of the Deconvolution Problem
9.5 The Regularization Method
CHAPTER 10 MODEL VALIDATION
10.3 Validation Strategies
10.4 Good Practice in Good Modeling
CHAPTER 11 CASE STUDIES
11.1 Case Study 1: A Sum of Exponentials Tracer Disappearance Model
11.2 Case Study 2: Blood Flow Modeling
11.3 Case Study 3: Cerebral Glucose Modeling
11.4 Case Study 4: Models of the Ligand-Receptor System
11.5 Case Study 5: A Simulation Model of the Glucose-Insulin System
11.5.1 Model Formulation
11.5.2 Results
11.6 Case Study 6: A Model of Insulin Control
11.7 Case Study 7: Illustrations of Bayesian Estimation
INDEXExemplaires(2)
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Titre : Modelling methodology for physiology and medicine Type de document : texte imprimé Auteurs : Ewart Carson, Auteur ; Claudio Cobelli, Auteur Editeur : Amsterdam,Boston,Heidelberg... : Elsevier Academic Press Année de publication : 2001 Collection : Academic Press Series in Biomedical Engineering Importance : 421 p. Présentation : couv. ill. en coul., ill. Format : 24 cm. ISBN/ISSN/EAN : 978-0-12-160245-1 Langues : Anglais (eng) Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-04 Modélisation des systèmes physiologiques Résumé : Modelling Methodology for Physiology and Medicine offers a unique approach and an unprecedented range of coverage of the state-of-the-art, advanced modelling methodology that is widely applicable to physiology and medicine. The book opens with a clear and integrated treatment of advanced methodology for developing mathematical models of physiology and medical systems. Readers are then shown how to apply this methodology beneficially to real-world problems in physiology and medicine, such as circulation and respiration.
Builds upon and enhances the readers existing knowledge of modelling methodology and practice
Editors are internationally renowned leaders in their respective fieldsNote de contenu : Contents:
Chapter 1. An Introduction to Modelling Methodology
1.1 Introduction
1.2 The Need for Models
1.3 Approaches to Modelling
1.4 Simulation
1.5 Model Identification
Chapter 2. Control in Physiology And Medicine
2.1 Introduction
2.2 A Systems and Control Approach
2.3 Control Mechanisms in Physiology
2.4 Control System Representations of the Clinical Process
2.5 Control System Approaches to Drug Therapy Planning and Administration
Chapter 3. Deconvolution
3.1 Introduction
3.2 Problem Statement
3.3 Difficulty of the Deconvolution Problem
3.4 The Regularization Method
3.5 Other Deconvolution Methods
3.6 Conclusions
3.7 Acknowledgements
Chapter 4. A priori Identifiability of Physiological Parametric Models
4.1 Introduction
4.2 The System-Experiment Model
4.3 A Priori Identifiability
4.4 Available Methods
4.5 An Identifiability Algorithm for Nonlinear Models
4.6 An Identifiability Algorithm for Linear Compartmental Models
Appendix A: The Characteristic Set
Appendix B: THE Gröbner Basis
Chapter 5. Parameter Estimation
5.1 Introduction
5.2 Least Squares and Maximum Likelihood Estimators
5.3 Bayesian Estimator
5.4 Population Kinetic Analysis
5.5 Acknowledgement
Chapter 6. Tracer Experiment Design for Metabolic Fluxes Estimation in Steady and Nonsteady State
6.1 Introduction
6.2 Fundamentals
6.3 Accessible-Pool and System Fluxes
6.4 The Tracer Probe
6.5 Estimation of Tracee Fluxes in Steady State
6.6 Estimation of Nonsteady-State Fluxes
Chapter 7. Physiological Modelling of Positron Emission Tomography Images
7.1 Introduction
7.2 Modeling Strategies
7.3 Positron Emission Tomography Measurement Error
7.4 Models of Regional Glucose Metabolism
7.5 Models of [15O]H2O Kinetics to Assess Blood Flow
7.6 Models of the Ligand-Receptor System
Chapter 8. Identification and Physiological Interpretation of Aortic Impedance in Modelling
8.1 Introduction
8.2 The Modelling Process and Related Problems of Identifiability and Determinacy
8.3 Vascular Impedance
8.4 Data-Driven Models of Vascular Impedance (Frequency Response Technique)
8.5 Historical Development of Windkessel Models
8.6 Where Windkessel Models' Identification Meets Physiological Interpretation
8.7 Contradictions in Clinically Oriented Compliance Estimation Methods (How the Viscoelastic Windke
8.8 Distributed Description of Linear Arterial Systems to Infer Aortic Wave Reflection
8.9 Identifiability: A Key Issue in the Assessment of Physiological Relevance of T-Tube Model
Chapter 9. Mathematical Modelling of Pulmonary Gas Exchange
9.1 Standard Equations Used to Describe Gas Transport in the Lungs
9.2 Models of Diffusion Limitation
9.3 Models of Ventilation Perfusion Mismatch
9.4 Application of Mathematical Models of Ventilation, Perfusion, and Diffusion
Appendix A. GLossary
Appendix B. Calculations Necessary to Convert Inspired Gas at ATPD to BTPS
Chapter 10. Mathematical Models of Respiratory Mechanics
10.1 Introduction
10.2 Breathing Mechanics: Basic Concepts
10.3 First-Order Models
10.4 Second-Order Models
10.5 Respiratory Oscillation Mechanics
10.6 Simulation Models of Breathing Mechanics
Chapter 11. Insulin Modelling
11.1 Introduction
11.2 Models of Whole-body Insulin Kinetics
11.3 An Organ Model of Insulin Secretion
11.4 Estimation of Insulin Secretion by Deconvolution
11.5 A Structural Model to Estimate Insulin Secretion and Secretory Indices
11.6 Estimation of Hepatic Insulin Extraction
Chapter 12. Glucose Modeling
12.1 Introduction
12.2 Models of Whole-body Kinetics in Steady State
12.3 Models of Regional Kinetics in Steady State
12.4 Models of Whole-body Kinetics in Nonsteady State
12.5 Models of Glucose and Insulin Control on Glucose Metabolism
12.6 Simulation Models
Chapter 13. Blood-Tissue Exchange Modelling
13.1 Introduction
13.2 Experimental Approaches
13.3 Models of Blood-Tissue Exchange
IndexModelling methodology for physiology and medicine [texte imprimé] / Ewart Carson, Auteur ; Claudio Cobelli, Auteur . - Amsterdam,Boston,Heidelberg... : Elsevier Academic Press, 2001 . - 421 p. : couv. ill. en coul., ill. ; 24 cm.. - (Academic Press Series in Biomedical Engineering) .
ISBN : 978-0-12-160245-1
Langues : Anglais (eng)
Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-04 Modélisation des systèmes physiologiques Résumé : Modelling Methodology for Physiology and Medicine offers a unique approach and an unprecedented range of coverage of the state-of-the-art, advanced modelling methodology that is widely applicable to physiology and medicine. The book opens with a clear and integrated treatment of advanced methodology for developing mathematical models of physiology and medical systems. Readers are then shown how to apply this methodology beneficially to real-world problems in physiology and medicine, such as circulation and respiration.
Builds upon and enhances the readers existing knowledge of modelling methodology and practice
Editors are internationally renowned leaders in their respective fieldsNote de contenu : Contents:
Chapter 1. An Introduction to Modelling Methodology
1.1 Introduction
1.2 The Need for Models
1.3 Approaches to Modelling
1.4 Simulation
1.5 Model Identification
Chapter 2. Control in Physiology And Medicine
2.1 Introduction
2.2 A Systems and Control Approach
2.3 Control Mechanisms in Physiology
2.4 Control System Representations of the Clinical Process
2.5 Control System Approaches to Drug Therapy Planning and Administration
Chapter 3. Deconvolution
3.1 Introduction
3.2 Problem Statement
3.3 Difficulty of the Deconvolution Problem
3.4 The Regularization Method
3.5 Other Deconvolution Methods
3.6 Conclusions
3.7 Acknowledgements
Chapter 4. A priori Identifiability of Physiological Parametric Models
4.1 Introduction
4.2 The System-Experiment Model
4.3 A Priori Identifiability
4.4 Available Methods
4.5 An Identifiability Algorithm for Nonlinear Models
4.6 An Identifiability Algorithm for Linear Compartmental Models
Appendix A: The Characteristic Set
Appendix B: THE Gröbner Basis
Chapter 5. Parameter Estimation
5.1 Introduction
5.2 Least Squares and Maximum Likelihood Estimators
5.3 Bayesian Estimator
5.4 Population Kinetic Analysis
5.5 Acknowledgement
Chapter 6. Tracer Experiment Design for Metabolic Fluxes Estimation in Steady and Nonsteady State
6.1 Introduction
6.2 Fundamentals
6.3 Accessible-Pool and System Fluxes
6.4 The Tracer Probe
6.5 Estimation of Tracee Fluxes in Steady State
6.6 Estimation of Nonsteady-State Fluxes
Chapter 7. Physiological Modelling of Positron Emission Tomography Images
7.1 Introduction
7.2 Modeling Strategies
7.3 Positron Emission Tomography Measurement Error
7.4 Models of Regional Glucose Metabolism
7.5 Models of [15O]H2O Kinetics to Assess Blood Flow
7.6 Models of the Ligand-Receptor System
Chapter 8. Identification and Physiological Interpretation of Aortic Impedance in Modelling
8.1 Introduction
8.2 The Modelling Process and Related Problems of Identifiability and Determinacy
8.3 Vascular Impedance
8.4 Data-Driven Models of Vascular Impedance (Frequency Response Technique)
8.5 Historical Development of Windkessel Models
8.6 Where Windkessel Models' Identification Meets Physiological Interpretation
8.7 Contradictions in Clinically Oriented Compliance Estimation Methods (How the Viscoelastic Windke
8.8 Distributed Description of Linear Arterial Systems to Infer Aortic Wave Reflection
8.9 Identifiability: A Key Issue in the Assessment of Physiological Relevance of T-Tube Model
Chapter 9. Mathematical Modelling of Pulmonary Gas Exchange
9.1 Standard Equations Used to Describe Gas Transport in the Lungs
9.2 Models of Diffusion Limitation
9.3 Models of Ventilation Perfusion Mismatch
9.4 Application of Mathematical Models of Ventilation, Perfusion, and Diffusion
Appendix A. GLossary
Appendix B. Calculations Necessary to Convert Inspired Gas at ATPD to BTPS
Chapter 10. Mathematical Models of Respiratory Mechanics
10.1 Introduction
10.2 Breathing Mechanics: Basic Concepts
10.3 First-Order Models
10.4 Second-Order Models
10.5 Respiratory Oscillation Mechanics
10.6 Simulation Models of Breathing Mechanics
Chapter 11. Insulin Modelling
11.1 Introduction
11.2 Models of Whole-body Insulin Kinetics
11.3 An Organ Model of Insulin Secretion
11.4 Estimation of Insulin Secretion by Deconvolution
11.5 A Structural Model to Estimate Insulin Secretion and Secretory Indices
11.6 Estimation of Hepatic Insulin Extraction
Chapter 12. Glucose Modeling
12.1 Introduction
12.2 Models of Whole-body Kinetics in Steady State
12.3 Models of Regional Kinetics in Steady State
12.4 Models of Whole-body Kinetics in Nonsteady State
12.5 Models of Glucose and Insulin Control on Glucose Metabolism
12.6 Simulation Models
Chapter 13. Blood-Tissue Exchange Modelling
13.1 Introduction
13.2 Experimental Approaches
13.3 Models of Blood-Tissue Exchange
IndexExemplaires(2)
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Titre : Numerical methods in biomedical engineering Type de document : texte imprimé Auteurs : Stanley M. Dunn, Auteur ; Alkis Constantinides, Auteur ; Prabhas V. Moghe, Auteur Editeur : Amsterdam,Boston,Heidelberg... : Elsevier Academic Press Année de publication : 2006 Collection : Academic Press Series in Biomedical Engineering Importance : 615 p. Présentation : couv. ill. en coul., ill. Format : 24,7 cm. ISBN/ISSN/EAN : 978-0-12-186031-8 Langues : Anglais (eng) Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-04 Modélisation des systèmes physiologiques Résumé : Numerical Modeling in Biomedical Engineering brings together the integrative set of computational problem solving tools important to biomedical engineers. Through the use of comprehensive homework exercises, relevant examples and extensive case studies, this book integrates principles and techniques of numerical analysis. Covering biomechanical phenomena and physiologic, cell and molecular systems, this is an essential tool for students and all those studying biomedical transport, biomedical thermodynamics & kinetics and biomechanics.
· Supported by Whitaker Foundation Teaching Materials Program; ABET-oriented pedagogical layout
· MATLAB problem sets and examples available electronically; UNIX, Windows, Mac OS compatible
· Extensive hands-on homework exercisesNote de contenu : Table of contents
Preface
Organization and Outline of the Book
Part I: Fundamentals
Chapter 1 Modeling Biosystems
1.1 Biomedical Engineering
1.2 Fundamental Aspects of Biomedical Engineering
1.3 Constructing Engineering Models
1.4 Examples of Solving Biomedical Engineering Models by Computer
1.5 Overview of the Text
1.6 Lessons Learned in this Chapter
1.7 Problems
Chapter 2 Introduction to Computing
2.1 Introduction
2.2 The Role of Computers in Biomedical Engineering
2.3 Programming Language Tools and Techniques
2.4 Fundamentals of Data Structures for MATLAB
2.5 An Introduction to Object-Oriented Systems
2.6 Analyzing Algorithms and Programs
Chapter 3 Concepts of Numerical Analysis
3.1 Scientific Computing
3.2 Numerical Algorithms and Errors
3.3 Taylor Series
3.4 Keeping Errors Small
3.5 Floating-Point Representation in MATLAB
Part II: Steady-State Behavior
Chapter 4 Linear Models of Biological Systems
4.2 Examples of Linear Biological Systems
4.3 Simultaneous Linear Algebraic Equations
4.4 The Gauss-Jordan Reduction Method
4.5 Iterative Approach for Solution of Linear Systems
Chapter 5 Nonlinear Equations in Biomedical Engineering
5.2 General Form of Nonlinear Equations
5.3 Examples of Nonlinear Equations in Biomedical Engineering
5.4 The Method of Successive Substitution
5.5 The Method of False Position (Linear Interpolation)
5.6 The Newton-Raphson Method
5.7 Newton’s Method for Simultaneous Nonlinear Equations
Part III: Dynamic Behavior
Chapter 6 Finite Difference Methods, Interpolation and Integration
6.2 Symbolic Operators
6.3 Backward Finite Differences
6.4 Forward Finite Differences
6.5 Central Finite Differences
6.6 Interpolating Polynomials
6.7 Interpolation of Equally Spaced Points
6.8 Interpolation of Unequally Spaced Points
6.9 Integration Formulas
6.10 The Newton-Cotes Formulas of Integration
Chapter 7 Dynamic Systems: Ordinary Differential Equations
7.2 Classification of Ordinary Differential Equations
7.3 Transformation to Canonical Form
7.4 Nonlinear Ordinary Differential Equations
7.5 Linear Ordinary Differential Equations
7.6 Steady-State Solutions and Stability Analysis
7.7 Numerical Stability and Error Propagation
7.8 Advanced Examples
Chapter 8 Dynamic Systems: Partial Differential Equations
8.2 Examples of PDEs in Biomedical Engineering
8.3 Classification of Partial Differential Equations
8.4 Initial and Boundary Conditions
8.5 Solution of Partial Differential Equations
8.6 Polar Coordinate Systems
8.7 Stability Analysis
8.8 PDE Toolbox in MATLAB
Part IV: Modeling Tools and Applications
Chapter 9 Measurements, Models and Statistics
9.1 The Role of Numerical Methods
9.2 Measurements, Errors and Uncertainty
9.3 Descriptive Statistics
9.4 Inferential Statistics
9.5 Least Squares Modeling
9.6 Curve Fitting
9.7 Fourier Transforms
Chapter 10 Modeling Biosystems
10.1 Numerical Modeling of Bioengineering Systems
10.2 PhysioNet, PhysioBank, and PhysioToolkit
10.2.1 ECG simulation
10.3 Signal Processing: EEG Data
10.4 Diabetes and Insulin Regulation
10.5 Renal Clearance
10.6 Correspondence Problems and Motion Estimation
10.7 PHYSBE Simulations
Appendices
Appendix A: Introduction to MATLAB
Appendix B: Introduction to Simulink
Appendix C: Review of Linear Algebra and Related MATLAB Commands
Appendix D: Analytical Solutions of Differential Equations
Appendix E: Numerical Stability and Other Topics
IndexNumerical methods in biomedical engineering [texte imprimé] / Stanley M. Dunn, Auteur ; Alkis Constantinides, Auteur ; Prabhas V. Moghe, Auteur . - Amsterdam,Boston,Heidelberg... : Elsevier Academic Press, 2006 . - 615 p. : couv. ill. en coul., ill. ; 24,7 cm.. - (Academic Press Series in Biomedical Engineering) .
ISBN : 978-0-12-186031-8
Langues : Anglais (eng)
Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-04 Modélisation des systèmes physiologiques Résumé : Numerical Modeling in Biomedical Engineering brings together the integrative set of computational problem solving tools important to biomedical engineers. Through the use of comprehensive homework exercises, relevant examples and extensive case studies, this book integrates principles and techniques of numerical analysis. Covering biomechanical phenomena and physiologic, cell and molecular systems, this is an essential tool for students and all those studying biomedical transport, biomedical thermodynamics & kinetics and biomechanics.
· Supported by Whitaker Foundation Teaching Materials Program; ABET-oriented pedagogical layout
· MATLAB problem sets and examples available electronically; UNIX, Windows, Mac OS compatible
· Extensive hands-on homework exercisesNote de contenu : Table of contents
Preface
Organization and Outline of the Book
Part I: Fundamentals
Chapter 1 Modeling Biosystems
1.1 Biomedical Engineering
1.2 Fundamental Aspects of Biomedical Engineering
1.3 Constructing Engineering Models
1.4 Examples of Solving Biomedical Engineering Models by Computer
1.5 Overview of the Text
1.6 Lessons Learned in this Chapter
1.7 Problems
Chapter 2 Introduction to Computing
2.1 Introduction
2.2 The Role of Computers in Biomedical Engineering
2.3 Programming Language Tools and Techniques
2.4 Fundamentals of Data Structures for MATLAB
2.5 An Introduction to Object-Oriented Systems
2.6 Analyzing Algorithms and Programs
Chapter 3 Concepts of Numerical Analysis
3.1 Scientific Computing
3.2 Numerical Algorithms and Errors
3.3 Taylor Series
3.4 Keeping Errors Small
3.5 Floating-Point Representation in MATLAB
Part II: Steady-State Behavior
Chapter 4 Linear Models of Biological Systems
4.2 Examples of Linear Biological Systems
4.3 Simultaneous Linear Algebraic Equations
4.4 The Gauss-Jordan Reduction Method
4.5 Iterative Approach for Solution of Linear Systems
Chapter 5 Nonlinear Equations in Biomedical Engineering
5.2 General Form of Nonlinear Equations
5.3 Examples of Nonlinear Equations in Biomedical Engineering
5.4 The Method of Successive Substitution
5.5 The Method of False Position (Linear Interpolation)
5.6 The Newton-Raphson Method
5.7 Newton’s Method for Simultaneous Nonlinear Equations
Part III: Dynamic Behavior
Chapter 6 Finite Difference Methods, Interpolation and Integration
6.2 Symbolic Operators
6.3 Backward Finite Differences
6.4 Forward Finite Differences
6.5 Central Finite Differences
6.6 Interpolating Polynomials
6.7 Interpolation of Equally Spaced Points
6.8 Interpolation of Unequally Spaced Points
6.9 Integration Formulas
6.10 The Newton-Cotes Formulas of Integration
Chapter 7 Dynamic Systems: Ordinary Differential Equations
7.2 Classification of Ordinary Differential Equations
7.3 Transformation to Canonical Form
7.4 Nonlinear Ordinary Differential Equations
7.5 Linear Ordinary Differential Equations
7.6 Steady-State Solutions and Stability Analysis
7.7 Numerical Stability and Error Propagation
7.8 Advanced Examples
Chapter 8 Dynamic Systems: Partial Differential Equations
8.2 Examples of PDEs in Biomedical Engineering
8.3 Classification of Partial Differential Equations
8.4 Initial and Boundary Conditions
8.5 Solution of Partial Differential Equations
8.6 Polar Coordinate Systems
8.7 Stability Analysis
8.8 PDE Toolbox in MATLAB
Part IV: Modeling Tools and Applications
Chapter 9 Measurements, Models and Statistics
9.1 The Role of Numerical Methods
9.2 Measurements, Errors and Uncertainty
9.3 Descriptive Statistics
9.4 Inferential Statistics
9.5 Least Squares Modeling
9.6 Curve Fitting
9.7 Fourier Transforms
Chapter 10 Modeling Biosystems
10.1 Numerical Modeling of Bioengineering Systems
10.2 PhysioNet, PhysioBank, and PhysioToolkit
10.2.1 ECG simulation
10.3 Signal Processing: EEG Data
10.4 Diabetes and Insulin Regulation
10.5 Renal Clearance
10.6 Correspondence Problems and Motion Estimation
10.7 PHYSBE Simulations
Appendices
Appendix A: Introduction to MATLAB
Appendix B: Introduction to Simulink
Appendix C: Review of Linear Algebra and Related MATLAB Commands
Appendix D: Analytical Solutions of Differential Equations
Appendix E: Numerical Stability and Other Topics
IndexExemplaires(4)
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