Results 221 to 230 of about 263,702 (262)

Receiver Operator Characteristic (ROC) Curves

Infection Control & Hospital Epidemiology, 1988
The goal of diagnostic testing is to identify patients with a particular disease. Often, it is just as important that the test not mistakenly identify healthy persons as having disease. For example, a new test for the acquired immunodeficiency syndrome (AIDS) might identify 99.99% of all patients infected with the human ...
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Statistical Approaches to the Analysis of Receiver Operating Characteristic (ROC) Curves

Medical Decision Making, 1984
In this article we review published and some unpublished work in statistical analyses of ROC curves. We describe both single and joint indices and indicate the approaches that have been taken to consider between-reader variations and correlations, within-reader variations, and variations and correlations between cases.
B J, McNeil, J A, Hanley
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Receiver Operating Characteristic (ROC) Curves: The Basics and Beyond

Hospital Pediatrics
Diagnostic tests and clinical prediction rules are frequently used to help estimate the probability of a disease or outcome. How well a test or rule distinguishes between disease or no disease (discrimination) can be measured by plotting a receiver operating characteristic (ROC) curve and calculating the area under it (AUROC).
Pearl W, Chang, Thomas B, Newman
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ROC-ing along: Evaluation and interpretation of receiver operating characteristic curves

Surgery, 2016
It is vital for clinicians to understand and interpret correctly medical statistics as used in clinical studies. In this review, we address current issues and focus on delivering a simple, yet comprehensive, explanation of common research methodology involving receiver operating characteristic (ROC) curves. ROC curves are used most commonly in medicine
Jane V, Carter, Jianmin, Pan, Shesh N, Rai, Susan, Galandiuk   +3 more
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Local linear smoothing of receiver operating characteristic (ROC) curves

Journal of Statistical Planning and Inference, 2004
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Peng, Liang, Zhou, Xiao-Hua
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ROC with confidence — a Perl program for receiver operator characteristic curves

Computer Methods and Programs in Biomedicine, 2001
Receiver operator characteristic (ROC) curves are recommended to assess the diagnostic value of tests depending on a single cut-off value of a continuous variable. These ROC curves show the true-positive rate (sensitivity) against the false-positive rate (1-specificity).
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The effect of random measurement error on receiver operating characteristic (ROC) curves

Statistics in Medicine, 2000
In this paper confidence intervals for the area under the ROC curve are adjusted for the presence of measurement error. A parametric normal model is assumed. The ratio of intra-individual to inter-individual variance provides a relative measure of the amount of measurement error. An exact adjusted confidence interval is developed for the equal variance
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An Evaluation of Methods for Estimating the Area Under the Receiver Operating Characteristic (ROC) Curve

Medical Decision Making, 1985
The area under the receiver operating characteristic (ROC) curve serves as one means for evaluating the performance of diagnostic and predictive test systems. The most commonly used method for estimating the area under an ROC curve utilizes the maximum-likelihood-estimation technique, and a nonparametric method to calculate the area under an ROC curve ...
R M, Centor, J S, Schwartz
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Receiver operating characteristic (ROC) curves: review of methods with applications in diagnostic medicine

Physics in Medicine & Biology, 2018
Abstract Receiver operating characteristic (ROC) analysis is a tool used to describe the discrimination accuracy of a diagnostic test or prediction model. While sensitivity and specificity are the basic metrics of accuracy, they have many limitations when characterizing test accuracy, particularly when comparing the accuracies of ...
Nancy A Obuchowski, Jennifer A Bullen
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Receiver operator characteristic (ROC) curves and non‐normal data: An empirical study

Statistics in Medicine, 1990
AbstractThis paper evaluates the performance of several diagnostic kits for assessing levels of serum prostatic acid phosphatase on patients at different stages of cancer of the prostate. Each patient was studied with several kits. We compare results obtained for receiver operator characteristic (ROC) curve methodology with data assumed to follow a ...
M J, Goddard, I, Hinberg
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