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The improvement in diagnostic confidence was assessed by receiver-operating characteristic (ROC) curve analysis by plotting the sensitivity (true-positive fraction) against 1-specificity (false-positive fraction).
This statistic measures model performance by plotting the sensitivity values – the true positive fraction of test points – against 1-specificity – the false-positive fraction for all available probability thresholds [53].
ROC curves were thereafter generated by plotting the sensitivity vs. 1-specificity.
Receiver operating curves (ROC) were drawn by plotting the sensitivity against 1 – specificity for different cutoff values.
The ROC curves were obtained by plotting the sensitivity of detecting RL as a function of [1 minus the specificity].
Traditional ROC curves are constructed by plotting the sensitivity versus 1-specificity for various decision thresholds of a test.
Similar(31)
The curves were constructed by plotting the sensitivities of the elements as a function of their atomic number.
7, 11 Caution needs to be exercised, however, when making this comparison as our ROC curve was calculated by varying the cut-off used on the CI + PI index, whereas Mitchell et al. generated an ROC curve by plotting the sensitivities and specificities reported in eight published reports of variable size and quality.
The true ROC curve is generated by plotting the true sensitivity on the vertical axis versus one minus the true specificity on the horizontal axis.
The observed ROC curve is generated by plotting the observed sensitivity on the vertical axis versus one minus the observed specificity on the horizontal axis.
In the validation group, an AUC of 0.85 was determined by plotting the ROC of sensitivity vs. (1-specificity) (Figure 3).
More suggestions(15)
by plotting the reciprocal
by plotting the inhibition
by plotting the sample
by plotting the log
by plotting the conductance
by plotting the mean
by plotting the generalization
by plotting the deviance
by plotting the frequency
by plotting the amount
by plotting the relationship
by plotting the deformation
by plotting the incidence
by plotting the number
by decreasing the sensitivity
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