The receiver operating characteristic (ROC) curve displays the capacity of a marker or diagnostic test to discriminate between two groups of subjects, cases versus controls. We present a comprehensive suite of Stata commands for performing ROC analysis. Non-parametric, semiparametric and parametric estimators are calculated. Comparisons between curves are based on the area or partial area under...

Receiver operating characteristic (ROC) analysis provides the most comprehensive description of diagnostic accuracy available to date, because it estimates and reports all of the combinations of sensitivity and specificity that a diagnostic test is able to provide. After sketching the 6 levels at which diagnostic efficacy can be assessed, this paper explains the conceptual foundations of conven...

objective: when none of digital systems and scanners is accessible and it is essential to have digitized images of conventional radiographs, digital cameras can be used. the aim of this study was to investigate whether digital images obtained by different resolutions of a digital camera are matched to the original radiographs in evaluation of caries. methods: in this diagnostic accuracy in vitr...

Department of Photonics and The Institute of Electro-Optical Engineering, National Chiao Tung University, Hsinchu 300, Taiwan, ROC b Institute of Physics, National Chiao Tung University, Hsinchu 300, Taiwan, ROC Department of Materials Science and Engineering, National TsingHua University, Hsinchu 300, Taiwan, ROC Material and Chemical Research Laboratories, Industrial Technology Research Insti...

background identification of a normal range for biomarkers, based on pregnancy outcomes (caused by their high or low values) is of special importance in clinical studies. as some pregnancy outcomes can happen in both high and low levels of biomarkers, the receiver-operating characteristic (roc) curve is unsuitable for identifying these levels separately; rather, a statistical method is preferab...

Many different metrics are used in machine learning and data mining to build and evaluate models. However, there is no general theory of machine learning metrics, that could answer questions such as: When we simultaneously want to optimise two criteria, how can or should they be traded off? Some metrics are inherently independent of class and misclassification cost distributions, while other ar...

ROC! is a deterministic rewrite strategy language which includes the rewrite rulesas basic operators, and the deterministic choice and the repetition as high-level strategyoperators. In this paper we present a method which, for a given term rewriting system(TRS) R, constructs a new TRS R such that R-rewriting is equivalent (sound and com-plete) with R-rewriting constrained by RO...