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1 For comparison, the area under the receiver operating characteristic curve was used.
2 A receiver- operating characteristic curve was generated by comparison of cases and controls.
3 Receiver operating characteristic curves were used to derive optimal dosimetric planning constraints.
4 Results were evaluated by using multipatient, multireader receiver operating characteristic jack-knife analysis.
5 Cutoff scores of accurate determinants were estimated via receiver operating characteristic analyses.
6 Performances of the risk score models were estimated using receiver operating characteristic curves.
7 The area under the receiver- operating characteristic curve was used to evaluate diagnostic accuracy.
8 Predictive accuracy was quantified using receiver operating characteristic analysis and decision curve analysis.
9 Receiver operating characteristic analyses for detecting different tissue types were performed.
10 Receiver operating characteristic curves were then analyzed between different disease groups.
11 Receiver- operating characteristic curves were used to select cut-off values for dose-volume.
12 Scoring systems were derived from this data and compared using receiver- operating characteristic curves.
13 Platelet count thresholds were assessed by the use of receiver operating characteristic curves.
14 Classification performances were assessed by using logistic regression and receiver operating characteristic analysis.
15 Conventional, frequentist receiver operating characteristic curve analysis was conducted as a sensitivity analysis.
16 The discriminatory values of the various models were compared by receiver- operating characteristic curves.
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