The ROC curve is a plot of the true positive rate (sensitivity) against the false positive rate (1 - specificity) across a range of threshold values. Each point on the curve represents a sensitivity/specificity pair corresponding to a particular decision threshold. The area under the ROC curve (AUC) is often used as a summary measure of the test's performance.
