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- Probabilistic reasoning is used when we consider the diagnostic accuracy of tests in our clinical decisions. It is also called Bayesian reasoning, being based on Bayes’ theorem, in which the probability of a hypothesis is modified by further data..
www.bmj.com/content/339/bmj.b3823
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2017年8月10日 · The Bayesian approach, which is based on a noncontroversial formula that explains how existing evidence should be updated in light of new data, 1 keeps statistics in the realm of the self-contained mathematical subject of probability in which every unambiguous question has a unique answer—even if it is hard to find. 2 The classical approach, whi...
- John A. Bittl, Yulei He
- 2017
2023年4月20日 · We start with an intuitive introduction to Bayesian reasoning. Then we introduce Bayes’ theorem, which is essential to the Bayesian framework. Using key concepts and definitions within both frequentist and Bayesian frameworks, we illustrate how Bayesian methods facilitate the interpretations of statistical results.
- 10.1007/s43441-023-00515-3
- 2023
- Ther Innov Regul Sci. 2023; 57(3): 402-416.
2020年9月1日 · We explain why such probabilistic reasoning is so important. We then acknowledge that the rule is quite abstract and may be difficult to use, and we offer a guideline to overcome this difficulty. We illustrate our text with an example from the mental health
- Bea Tiemens, Renée Wagenvoorde, Cilia Witteman
- 2020
2010年11月16日 · The purpose of this paper is to present and explore the simplest forms of Bayes’ Rule, and to explain how it may be used in practical reasoning, especially in clinical settings. A great deal has been written about the importance of conditional probability in diagnostic situations.
- Chris F Westbury
- 2010
2021年6月1日 · Bayes’ theorem is a quantitative method for calculating post-test probability using the pretest probability and the sensitivity and specificity of the test. The theorem is derived from the definition of conditional probability and from the properties of probability (see the Appendix to this chapter for the derivation).
- Douglas K. Owens, Douglas K. Owens, Harold C. Sox
- 2006
Bayes' rule represents the probabilistic nature of diagnostic reasoning in the form of a mathematical equation. This equation expresses the relationship between probabilities operating during the diagnostic process, showing that the most important determinants of
2021年3月1日 · Bayes' rule represents the probabilistic nature of diagnostic reasoning in the form of a mathematical equation. This equation expresses the relationship between probabilities operating during the diagnostic process, showing that the most important determinants of the posterior probability of disease are the prior probability and the ...
