[Methods of selection of cutoff points in the development and interpretation of diagnostic tests].

L Strnad, J Tosner
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Abstract

Problems related to the optimization of diagnosis making are scrutinized. Applied immunological tests for diagnosis of ovarian cancers are used as an example of ROC curve calculation. Moreover, sensitivity and specificity grades are computed in order to obtain the optimum of diagnostical robustness. The ROC analysis is supplemented with application of Bayes diagnostical algorithm. The analysis is given also of other problems concerning with implementation of quantitative characteristics in the course of diagnostical decision making.

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[诊断试验发展和解释中截断点的选择方法]。
讨论了与优化诊断有关的问题。应用免疫学试验诊断卵巢癌作为ROC曲线计算的一个例子。此外,还计算了敏感性和特异性等级,以获得最佳的诊断稳健性。在ROC分析的基础上辅以贝叶斯诊断算法的应用。分析了在诊断决策过程中运用定量特征所涉及的其他问题。
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