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Evaluation and Comparison of Diagnostic Test Performance Based on Information Theory

机译:基于信息论的诊断测试性能评估与比较

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A fundamental concept of information theory, relative entropy and mutual information, is directly applicable to evaluation of diagnostic test performance. The aim of this study is to demonstrate how basic concepts in information theory apply to the problem of quantifying major depressive disorder diagnostic test performance. In this study, the performances of the Dexamethasone Suppression Test-DST and the Thyroid-Stimulating Hormone Test-TSH, two of the diagnosis tests of Major Depressive Disorder, are evaluated with the method of Information Theory. The amount of information gained by performing a diagnostic test can be quantified by calculating the relative entropy between the posttest and pretest probability distributions. And also demonstrates that diagnostic test performance can be quantified as the average amount of information the test result provides about the disease state. It is aimed that this study will hopefully give various points of view to the researchers who want to make research on this subject by explaining how the tests used for the diagnosis of various diseases are evaluated with this way.
机译:信息论的基本概念,相对熵和互信息,可直接用于诊断测试性能的评估。这项研究的目的是证明信息论中的基本概念如何应用于量化重度抑郁症诊断测试表现的问题。在这项研究中,地塞米松抑制试验-DST和甲状腺刺激激素试验-TSH(两种主要抑郁症的诊断试验)的性能用信息论方法进行了评估。通过执行诊断测试获得的信息量可以通过计算后测和前测概率分布之间的相对熵来量化。并且还证明诊断测试的性能可以量化为测试结果提供的有关疾病状态的平均信息量。目的是希望通过解释如何以此方式评估用于诊断各种疾病的测试方法,希望给希望对此主题进行研究的研究人员以各种观点。

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