Optimal Cut-point and Its Corresponding Youden Index to Discriminate Individuals Using Pooled Blood Samples

By Enrique F. Schisterman, Neil Perkins, Aiyi Liu, Howard D. Bondell. Epidemiology, 2005

1,164 citations recorded by the source corpus.

Subfields: Physiology, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/c330ac4c7df0f169422943bc5278df75fcb92fdb

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In Physiology

Xinhua Liu

In Statistics and Probability

Citations in the corpus

OptimalCutpoints: An R Package for Selecting Optimal Cutpoints in Diagnostic Tests (2014, background): “…the costs of incorrect classiﬁcations of the diagnosis, the generalized Youden index ( GYI , Geisser 1998; Greiner, Pfeiﬀer, and Smith 2000; Schisterman, Perkins, Liu, and Bondell 2005, both possibilities are included in the "Youden" method of the package); eﬃciency or proportion of cases…”
Improving protein disorder prediction by deep bidirectional long short‐term memory recurrent neural networks (2016, background): “…(AUC) as it is an indication of the margin between the random predictor (where S e ¼ 1 (cid:4) S p ) and the obtained ROC for the chosen threshold (Schisterman et al. , 2005): where W o and W d are the ratio of disordered and ordered residues, respectively, and N d and N o are the total number…”
What is an ROC curve? (2017, methodology): “known as the Youden Index.[4] We illustrate how this is done using Figure 1.”
2016 ACR-EULAR Classification Criteria for primary Sjögren’s Syndrome: A Consensus and Data-Driven Methodology Involving Three International Patient Cohorts (2016, methodology): “For each candidate item, 2 cutoff values were identified using a generalized Youden index (36).”
The inconsistency of "optimal" cutpoints obtained using two criteria based on the receiver operating characteristic curve. (2006, background): “Additional motivation for using J is an ever-increasing body of supporting literature (9, 15, 19).”
Defining an Optimal Cut-Point Value in ROC Analysis: An Alternative Approach (2017, background): “These values of μ1 guarantee a wide variety of classification accuracies, ranging from a poor to a high one [7, 11, 13].”
Classification accuracy and cut point selection (2012, methodology): “Recently, the Youden index-based method of cut point selection has been extended to accommodate various cases including a pooled sample [10], a biomarker subject to measurement error [11], cases where the observations are affected by a lower limit of detection [12], or where a marker has mass at zer”