Aspinall P, Hill A R
Ophthalmic Physiol Opt. 1984;4(1):31-8.
In patient management, clinical decisions follow a logical sequence which can be formally expressed as a decision tree in which the uncertainties associated with each alternative outcome may be made explicit using Bayes' theorem. Where test data is used in the formulation of a decision, the uncertainty associated with the information it conveys may be modified by changing the pass/fail criterion to alter the false positive and false negative error rate. Classical procedures based on information theory are described to illustrate how this may be achieved for any test. When hard data is not available to permit such an approach, the clinician must rely on his own past experience or that of a colleague. Several methods are available for quantifying such experience by estimating subjective probabilities associated with an action or test result. Two simple methods are described for deriving subjective probabilities for subsequent use within a Bayesian decision model.
在患者管理中，临床决策遵循一个逻辑顺序，这个顺序可以用决策树的形式正式表示出来，其中与每个替代结果相关的不确定性可以使用贝叶斯定理明确表示。在决策制定过程中使用测试数据时，通过改变通过/失败标准来改变假阳性和假阴性错误率，可以修改与该信息相关的不确定性。描述了基于信息论的经典程序，以说明如何对任何测试实现这一点。当没有硬数据允许采用这种方法时，临床医生必须依靠自己或同事过去的经验。有几种方法可用于通过估计与行动或测试结果相关的主观概率来量化此类经验。描述了两种简单的方法来推导主观概率，以便在贝叶斯决策模型中后续使用。
