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A novel delta check method for detecting laboratory errors

机译:一种检测实验室误差的新型增量检查方法

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Investigating the variation of clinical measurements of patients over time is a common technique, known as delta check, for detecting laboratory errors. They are based on the expected biological variations and machine imprecision, where the latter varies for different concentrations of the analytes. Here, we present a novel delta check method in the form of composite thresholding, and provide its sufficient statistics by constructing the corresponding discriminant function, which enables us to use statistical and learning analysis tools. Using the scores obtained from such a discriminant function, we statistically study the performance of our algorithm on a labeled data set for the purpose of detecting lab errors.
机译:调查患者临床测量值随时间的变化是一种用于检测实验室错误的常用技术,称为增量检查。它们基于预期的生物学变化和机器不精确度,其中机器不精确度随分析物浓度的不同而变化。在这里,我们以复合阈值的形式提出了一种新颖的增量检查方法,并通过构造相应的判别函数来提供其足够的统计信息,从而使我们能够使用统计和学习分析工具。使用从这种判别函数获得的分数,我们统计地研究了我们在标记数据集上算法的性能,以检测实验室错误。

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