Area under the receiver operating characteristic

AUROC area under the receiver operator characteristic... 

Discrimination can be summarized by various single statistics, such as the area under the receiver operating characteristic curve (or the equivalent C statistic), measures, or the d statistic, although all of these measures have limitations (Royston and Sauerbrei 2004 Altman and Royston 2007 Lewis 2007). 

Evaluation of the selectivity of each model by one of the discrimination measures, e.g., area under the receiver operating characteristic (ROC) curve (AUC) ... 

AUC Area under the receiver operating characteristic curve... 

Cl, confidence interval TIA, transient ischemic attack CT, computed tomography ECG, electrocardiography AUC-ROC, area under the curve of the received operator characteristic... 

In addition, the Area Under the Curves (AUC) of the Receiver Operating Characteristic (ROC) curves were calculated as a quantitative measure for sensitivity and specificity of BIS to estimate the BAC. In a ROC curve, the True Positive Rate (TPR, sensitivity) is plotted against the False Positive Rate (FPR, 1-specificity). The TPR defines how many correct positive results occur among all positive samples and the FPR defines how many incorrect positive results occur among all negative samples. The AUC is then calculated as follows ... 

When a new test is developed or an old test is applied to a new clinical question, users need information about the extent of agreement of the test s results with the correct diagnoses of patients. For this purpose, researchers design studies in which results from the new test are compared with the results obtained with the reference standard on the same patients. The results of the comparison can be expressed in a number of ways, including sensitivity and specificity, predictive values, likelihood ratios, diagnostic odds ratios, and areas under receiver operating characteristic (ROC) curves (see Chapter 15). We will refer to such studies as diagnostic accuracy studies. 

The aim of BPS-MS approach presented here can be summarized by comparing the simulated receiver operator characteristic (ROC) curves shown in Figure 1. Each additional dimension of analysis (a distinct pulse shape, that yields distinct mass spectrum) enlarges the area under the curve and therefore the confidence of the measurement. 

Table 6.5 summarizes the results for each outcome prediction variable for the evaluation step. Accuracies obtained using the ANN model was inferior to those using SVM, RF, and LDA. Based on McNemar s test, fc-NN performed the worst for predicting source of bleeding. LDA appeared to demonstrate a good overall performance with regards to sensitivity, specificity, PPV, NPV, and accuracy (Table 6.5). ROC (receiver operating characteristic) curves are calculated and areas under the curve (AUC) are compared for each of the models. An ROC curve is a...

Receiver operating characteristic (ROC) curves for the two modalities, based on a continuous likelihood of malignancy scale for each finding from 0 to 100%, were not significantly different (p = 0.18). The trend in area under the curve favored film (Fig. 9.1). 

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