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Table of Contents
Intro
Preface
Contents
List of Figures
1 Evidence and Decision-Making
1.1 Introduction
1.2 Evidence-Based Medicine (EBM)
1.3 Theories of Decision-Making
1.4 Rational Decision-Making
1.5 Threshold Model of Decision-Making: The Linchpin Between EBM and Decision-Making
References
2 Making Decisions When No Further Diagnostic Testing is Available
2.1 Introduction
2.2 Expected Utility Theory Threshold Model
2.3 Threshold Model When the Diagnosis Is Not Certain, and Outcomes Are Not Certain
2.4 Threshold Models When the Diagnosis Is Certain, but Health Outcomes (Utilities) Are Uncertain
References
3 Making Decisions When no Further Diagnostic Testing is Available (Expected Regret Theory Threshold Model)
3.1 Introduction
3.2 Acceptable Regret
References
4 Decision-Making When Diagnostic Testing is Available
4.1 Introduction
4.2 Threshold Modeling When Diagnostic Testing is Available
References
5 Formulating Management Strategies Using Fast-and-Frugal Trees (A Decision Tool to Transform Clinical Practice Guidelines and Clinical Pathways into Decision Support at the Point of Care)
5.1 Introduction
5.2 Fast-and-Frugal Trees
References
6 Using Decision Curve Analysis to Evaluate Testing and/or Predictive Modeling
6.1 Introduction
6.2 Illustrative Examples
References
7 Hybrid and Dual-Processing Threshold Decision Models
7.1 Hybrid Threshold Model
7.2 The Dual-Processing Threshold Model
References
8 Which Threshold Model?
8.1 Introduction
8.1.1 A Brief Review of the Principles of Medical Decision-Making
8.1.2 Different Theoretical Models Generate Different Recommendations
8.1.3 Contemporary Clinical Practice Represents an Environment Favoring the Overuse of Diagnostic and Treatment Interventions
8.1.4 Simple Versus Complex Models
8.1.5 Adhering to Practical Wisdom
References
9 Medical Decision-Making and Artificial Intelligence
9.1 Introduction
9.2 Machine Learning
9.3 Machine Learning and Clinical Care
9.4 AI Challenges and Limitations
9.5 Statistical and Decision-Theoretical View of Artificial Intelligence Modeling
9.6 Conclusions
References
Appendix
A.1 Expected Utility Theory
A.1.1 A Decision About Treatment (Rx) Versus No Treatment (NoRx): When the Diagnosis (Clinical Event) Is Not Certain and No Further Diagnostic (dx) Test Is Available
A.1.2 Rx Versus NoRx
A.1.3 Rx1 Versus Rx2: When Diagnosis Is Not Certain and No Further dx Test Is Available
A.1.4 Rx1 Versus Rx2: When Diagnosis Is Certain and No Further dx Test Is Available
Preface
Contents
List of Figures
1 Evidence and Decision-Making
1.1 Introduction
1.2 Evidence-Based Medicine (EBM)
1.3 Theories of Decision-Making
1.4 Rational Decision-Making
1.5 Threshold Model of Decision-Making: The Linchpin Between EBM and Decision-Making
References
2 Making Decisions When No Further Diagnostic Testing is Available
2.1 Introduction
2.2 Expected Utility Theory Threshold Model
2.3 Threshold Model When the Diagnosis Is Not Certain, and Outcomes Are Not Certain
2.4 Threshold Models When the Diagnosis Is Certain, but Health Outcomes (Utilities) Are Uncertain
References
3 Making Decisions When no Further Diagnostic Testing is Available (Expected Regret Theory Threshold Model)
3.1 Introduction
3.2 Acceptable Regret
References
4 Decision-Making When Diagnostic Testing is Available
4.1 Introduction
4.2 Threshold Modeling When Diagnostic Testing is Available
References
5 Formulating Management Strategies Using Fast-and-Frugal Trees (A Decision Tool to Transform Clinical Practice Guidelines and Clinical Pathways into Decision Support at the Point of Care)
5.1 Introduction
5.2 Fast-and-Frugal Trees
References
6 Using Decision Curve Analysis to Evaluate Testing and/or Predictive Modeling
6.1 Introduction
6.2 Illustrative Examples
References
7 Hybrid and Dual-Processing Threshold Decision Models
7.1 Hybrid Threshold Model
7.2 The Dual-Processing Threshold Model
References
8 Which Threshold Model?
8.1 Introduction
8.1.1 A Brief Review of the Principles of Medical Decision-Making
8.1.2 Different Theoretical Models Generate Different Recommendations
8.1.3 Contemporary Clinical Practice Represents an Environment Favoring the Overuse of Diagnostic and Treatment Interventions
8.1.4 Simple Versus Complex Models
8.1.5 Adhering to Practical Wisdom
References
9 Medical Decision-Making and Artificial Intelligence
9.1 Introduction
9.2 Machine Learning
9.3 Machine Learning and Clinical Care
9.4 AI Challenges and Limitations
9.5 Statistical and Decision-Theoretical View of Artificial Intelligence Modeling
9.6 Conclusions
References
Appendix
A.1 Expected Utility Theory
A.1.1 A Decision About Treatment (Rx) Versus No Treatment (NoRx): When the Diagnosis (Clinical Event) Is Not Certain and No Further Diagnostic (dx) Test Is Available
A.1.2 Rx Versus NoRx
A.1.3 Rx1 Versus Rx2: When Diagnosis Is Not Certain and No Further dx Test Is Available
A.1.4 Rx1 Versus Rx2: When Diagnosis Is Certain and No Further dx Test Is Available