The accuracy of a medical diagnostic tool depends on its specificity, the probability that it classifies a normal person as normal, and its sensitivity, the probability that it classifies a diseased person as diseased. The receiver operating characteristic (ROC) curve of such a tool is its sensitivity plotted against (1 specificity) as the threshold defining “normal” versus “diseased” ranges ov...

Receiver operating characteristic (ROC) curves and in particular the area under the curve (AUC), are widely used to examine the effectiveness of diagnostic markers. Diagnostic markers and their corresponding ROC curves can be strongly influenced by covariate variables. When several diagnostic markers are available, they can be combined by a best linear combination such that the area under the R...

Receiver Operating Characteristics (ROC) curve serves as a statistical tool to measure the quality of Biomarker in 5 accessing the accuracy of any diagnostic test. This paper portrays the historical background of ROC curve and reviews various 6 parametric methods adopted for fitting the ROC curve till date. The parametric ROC models that are considered in this paper 7 are Bi-Normal, Bi-Gamma, B...

ROC curve analysis is a fundamental tool for evaluating the performance of a marker in a number of research areas, e.g., biomedicine, bioinformatics, engineering etc., and is frequently used for discriminating cases from controls. There are a number of analysis tools which are used to guide researchers through their analysis. Some of these tools are commercial and provide basic methods for ROC ...

The receiver operating characteristic (ROC) curve is used for classification between two populations. Usually two independent random samples from the populations with absolutely continuous cumulative distribution functions (CDF) F and G are considered. Then the ROC curve is defined as ROC(t) = 1−G(F−1(1− t)) for 0 < t < 1 if the inverse F−1 exists. Classical ROC curve estimator is based on empi...

The ROC (Receiver Operating Chracteristic) curves are frequently used for different diagnostic purposes. There are several different approaches how to find the suitable estimate of the ROC curve in binormal model. The effective methods which can be used when the sample sizes are small are still very demanded in different applications. In the paper the binormal model is assumed and the parametri...

Aims: To evaluate different algorithms used to analyse retinal nerve fibre layer thickness (RNFL) data obtained by scanning laser polarimetry, in order to compare their relative abilities to discriminate between patients with glaucomatous localised nerve fibre layer defects and normal subjects. Methods: 48 eyes of 48 glaucomatous patients with localised RNFL defects and 53 eyes of 53 healthy su...

BACKGROUND Basic courses in most medical schools assess students' performance by conferring scores. The objective of this work is to use a large score databank for the early identification of students with low performance and to identify course trends based on the mean of students' grades. METHODOLOGY/PRINCIPAL FINDINGS We studied scores from 2,398 medical students registered in courses over ...