Biomedical Decision Making: Probabilistic Clinical Reasoning



After reading this chapter, you should know the answers to these questions:
  • How is the concept of probability useful for understanding test results and for making medical decisions that involve uncertainty?

  • How can we characterize the ability of a test to discriminate between disease and health?

  • What information do we need to interpret test results accurately?

  • What is expected-value decision making? How can this methodology help us to understand particular medical problems?

  • What are utilities, and how can we use them to represent patients’ preferences?

  • What is a sensitivity analysis? How can we use it to examine the robustness of a decision and to identify the important variables in a decision?

  • What are influence diagrams? How do they differ from decision trees?


Decision Analysis Treatment Threshold Positive Test Result Standard Gamble Pretest Probability 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag London 2014

Authors and Affiliations

  1. 1.VA Palo Alto Health Care SystemPalo AltoUSA
  2. 2.Henry J. Kaiser Center for Primary Care and Outcomes Research/Center for Health PolicyStanford UniversityStanfordUSA
  3. 3.Dartmouth InstituteGeisel School of Medicine at Dartmouth, Dartmouth CollegeWest LebanonUSA

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