Mild, Moderate and Severe Cut-Points for the Respiratory Distress Observation Scale: A Receiver Operating Characteristic Curve Analysis (TH361A)

Receiver Operating Characteristic (ROC) Curve Analysis for Medical Diagnostic Test Evaluation

This review provides the basic principle and rational for ROC analysis of rating and continuous diagnostic test results versus a gold standard. Derived indexes of accuracy, in particular area under the curve (AUC) has a meaningful interpretation for disease classification from healthy subjects. The methods of estimate of AUC and its testing in single diagnostic test and also comparative studies...

Application of Receiver Operating Characteristic Curve for Pipeline Reliability Analysis

Structural reliability analysis of buried pipeline systems is one of the fundamental issues for water and wastewater asset managers. Measuring the accuracy of a reliability analysis or a failure prediction technique is an effective approach to enhancing its applicability and provides guidance on selection of reliability or failure prediction methods. The determination of threshold value for a p...

part 5: receiver operating characteristic curve and area under the curve

multiple diagnostic tools are used by emergency physicians, every day. in addition, new tools are evaluated to obtain more accurate methods and reduce time or cost of conventional ones. in the previous parts of this educational series, we described diagnostic performance characteristics of diagnostic tests including sensitivity, specificity, positive and negative predictive values, and likeliho...

An intuitive approach to receiver operating characteristic curve analysis.

Receiver operating characteristic curves and optimal Bayesian operating points

Receiver operating characteristic curve is a standard method for reporting performance of a system. In this paper we show how to choose the optimal operating point when we are given a receiver operating curve, the prior probabilities, and the economic gain matrix. Unlike earlier methods, we make no assumptions regarding underlying distributions.