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. Author manuscript; available in PMC: 2020 Dec 1.
Published in final edited form as: Br J Dermatol. 2019 Jul 7;181(6):1146–1155. doi: 10.1111/bjd.17917

Figure 1. Sensitivity, specificity, and receiver-operating characteristic curves.

Figure 1.

a. Examples of receiver-operating characteristic curves (ROC). The red line demonstrates a ROC with an area under the curve (AUC) of 0.5, indicating a predictor with no ability to discriminate cases from controls. The solid and dashed blue lines indicate increased AUC, and thus greater predictive ability.

b. For a given dichotomous outcome and predictor, the proportions of true positive, false positive, true negative, and false negative cases may be defined. Sensitivity is defined as the true positive fraction, or the proportion of cases correctly identified by the test (predictor) as having the outcome. Specificity is defined as the true negative fraction, or the proportion of cases correctly identified by the test as not having the outcome.