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Tutorials : ROC curve

What is a ROC curve?

The Receiver Operating Characteristic (ROC) curve is a graphical plot of the sensitivity versus 1 - specificity across all possible threshold values of the marker. The sensitivity is the ability of the test to detect the cases accurately. The specificity is the ability of the test to detect the controls accurately.

How to interpret the AUC?

The area under the ROC curve (AUC) can be interpreted as the probability that among two randomly chosen subjects, one case and one control, the value of the marker is higher for the case than for the control. Therefore, an AUC of 0.5 (50%) indicates that the marker is non-informative. An increase in the AUC indicates an improvement in discriminative capacities, with a maximum of 1.0 (100%).

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Le laboratoire SPHERE (methodS for Patients-centered outcomes and HEalth REsearch, INSERM UMR 1246, Université de NantesUniversité de Tours) et la société IDBC (groupe A2com) ont décidé de créer ensemble le Laboratoire Commun RISCA (Research in Informatics and Statistics for Cohort-based Analyses)