2005
DOI: 10.1016/j.athoracsur.2004.09.040
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Summary Receiver Operating Characteristic Curve Analysis Techniques in the Evaluation of Diagnostic Tests

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Cited by 418 publications
(311 citation statements)
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“…However, the specificity of 0.97 is relatively high to confirm diagnosis. The SROC curve presents as a summary of the diagnostic performance, which shows the trade-off between sensitivity and specificity [26]. Our SROC analysis showed that the maximum joint of sensitivity and specificity was 0.91 and an AUC of 0.96, suggesting a high overall accuracy.…”
Section: Discussionmentioning
confidence: 76%
“…However, the specificity of 0.97 is relatively high to confirm diagnosis. The SROC curve presents as a summary of the diagnostic performance, which shows the trade-off between sensitivity and specificity [26]. Our SROC analysis showed that the maximum joint of sensitivity and specificity was 0.91 and an AUC of 0.96, suggesting a high overall accuracy.…”
Section: Discussionmentioning
confidence: 76%
“…Another indicator obtained to evaluate the quality of the test was the odds ratio, calculated on the basis of the sensitivity and specificity values. (22)(23)(24) The overall sensitivity and specificity values, together with their respective 95% CIs, were also found through the SROC curve. Using these values, we calculated the post-test probability for various, randomly determined prevalences of tuberculosis.…”
Section: Methodsmentioning
confidence: 99%
“…Size AUC>0.8, generally indicates that the test is accurate, and more close to the curve at the top left corner, which is the point (0, 1) the more accurate. The larger AUC makes more accurate diagnostic test (Jones and Athanasiou, 2005;Chaudron et al, 2010). However, for screening purposes, the value of higher sensitivity is preferred, although the AUC have the same size.…”
Section: Auc and Roc Curvesmentioning
confidence: 99%
“…The bigger ROC triangle, optimize combination of sensitivity and specificity (Jones and Athanasiou, 2005;Akobeng, 2007). ROC curve analysis is also a method used to evaluate the logistic regression model.…”
Section: Auc and Roc Curvesmentioning
confidence: 99%