OBJECTIVE To assess the cutoff values established by ROC curves to classify (18)F-NaF uptake as normal or malignant. MATERIALS AND METHODS PET/CT images were acquired 1 hour after administration of 185 MBq of (18)F-NaF. Volumes of interest (VOIs) were drawn on three regions of the skeleton as follows: proximal right humerus diaphysis (HD), proximal right femoral diaphysis (FD) and first verte...

Traditionally, the receiver operating characteristic (ROC) curve for a diagnostic test plots true positives (sensitivity) against false positives (one minus specificity). However, this representation brings with it several drawbacks. A transformation to positive and negative likelihood ratio co-ordinates, scaled by base-ten logarithms, offers several advantages. First we motivate the use of pos...

The receiver operating characteristic (ROC) curve has been a popular statistical tool for characterizing the discriminating power of a classifier, such as a biomarker or an imaging modality for disease screening or diagnosis. It has been recognized that the accuracy of a given procedure may depend on some underlying factors, such as subject's demographic characteristics or disease risk factors,...

Abstract Throughout science and technology, receiver operating characteristic (ROC) curves associated area under the curve ( $$\mathrm{AUC}$$ AUC ) measures constitute powerful tools for assessing predictive abilities of features, markers tests in binary classification problems. Despite its immense popularity...

The receiver operating characteristic (ROC) curve is widely used for diagnosing as well as for judging the discrimination ability of different statistical models. Although theories about ROC curves have been established and computation methods and computer software are available for cross-sectional design, limited research for estimating ROC curves and their summary statistics has been done for...

The receiver operating characteristics (ROC) curve is a standard statistical tool to characterize the accuracy of diagnostic tests when test results are continuous. It provides a complete description of test performance and a meaningful way to compare the performances of different tests. The empirical (nonparametric) ROC curve is the most popular estimator of the ROC curve. Semiparametric estim...

A receiver operating characteristic (ROC) curve is a plot of predictive model probabilities of true positives (sensitivity) as a function of probabilities of false positives (1 – specificity) for a set of possible cutoff points. Some of the SAS/STAT procedures do not have built-in options for ROC curves and there have been a few suggestions in previous SAS forums to address the issue by using e...

Receiver operating characteristic (ROC) curve is widely applied in measuring discriminatory ability of diagnostic or prognostic tests. This makes ROC analysis one of the most active research areas in medical statistics. Many parametric and semiparametric estimation methods have been proposed for estimating the ROC curve and its functionals. In this paper, we propose a fully nonparametric Bayesi...

Receiver-operating characteristic (ROC) analysis was originally developed during World War II to analyze classification accuracy in differentiating signal from noise in radar detection.1 Recently, the methodology has been adapted to several clinical areas heavily dependent on screening and diagnostic tests,2–4 in particular, laboratory testing,5 epidemiology,6 radiology,7–9 and bioinformatics.1...

Violent behaviour risk assessment is currently one of the most relevant research areas in the Psychology of Crime. Various scales for violence risk assessment have been developed in recent years through research on criminal careers and risk factors. One such instrument is the Sexual Violence Risk Assessment-20 (SVR-20), translated and adapted to Spanish by the Advanced Studies in Violence Group...