Literature DB >> 15505886

Ordered multiple-class ROC analysis with continuous measurements.

Christos T Nakas1, Constantin T Yiannoutsos.   

Abstract

Receiver operating characteristic (ROC) curves have been useful in two-group classification problems. In three- and multiple-class diagnostic problems, an ROC surface or hyper-surface can be constructed. The volume under these surfaces can be used for inference using bootstrap techniques or U-statistics theory. In this article, ROC surfaces and hyper-surfaces are defined and their behaviour and utility in multi-group classification problems is investigated. The formulation of the problem is equivalent to what has previously been proposed in the general multi-category classification problem but the definition of ROC surfaces here is less complex and addresses directly the narrower problem of ordered categories in the three-class and, by extension, the multi-class problem applied to continuous and ordinal data. Non-parametric manipulation of both continuous and discrete test data and comparison between two diagnostic tests applied to the same subjects are considered. A three-group classification example in the context of HIV neurological disease is presented and the results are discussed. 2004 John Wiley & Sons, Ltd.

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Year:  2004        PMID: 15505886     DOI: 10.1002/sim.1917

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  42 in total

1.  Parametric and non-parametric confidence intervals of the probability of identifying early disease stage given sensitivity to full disease and specificity with three ordinal diagnostic groups.

Authors:  Tuochuan Dong; Lili Tian; Alan Hutson; Chengjie Xiong
Journal:  Stat Med       Date:  2011-12-05       Impact factor: 2.373

2.  Evaluation of diagnostic accuracy in detecting ordered symptom statuses without a gold standard.

Authors:  Zheyu Wang; Xiao-Hua Zhou; Miqu Wang
Journal:  Biostatistics       Date:  2011-01-05       Impact factor: 5.899

3.  Performance analysis of three-class classifiers: properties of a 3-D ROC surface and the normalized volume under the surface for the ideal observer.

Authors:  Berkman Sahiner; Heang-Ping Chan; Lubomir M Hadjiiski
Journal:  IEEE Trans Med Imaging       Date:  2008-02       Impact factor: 10.048

4.  Validation of Monte Carlo estimates of three-class ideal observer operating points for normal data.

Authors:  Darrin C Edwards
Journal:  Acad Radiol       Date:  2013-07       Impact factor: 3.173

5.  The meaning and use of the volume under a three-class ROC surface (VUS).

Authors:  Xin He; Eric C Frey
Journal:  IEEE Trans Med Imaging       Date:  2008-05       Impact factor: 10.048

6.  Three-class ROC analysis--toward a general decision theoretic solution.

Authors:  Xin He; Brandon D Gallas; Eric C Frey
Journal:  IEEE Trans Med Imaging       Date:  2009-10-30       Impact factor: 10.048

7.  Application of three-class ROC analysis to task-based image quality assessment of simultaneous dual-isotope myocardial perfusion SPECT (MPS).

Authors:  Xin He; Xiyun Song; Eric C Frey
Journal:  IEEE Trans Med Imaging       Date:  2008-11       Impact factor: 10.048

8.  Exact confidence interval estimation for the difference in diagnostic accuracy with three ordinal diagnostic groups.

Authors:  Lili Tian; Chengjie Xiong; Chin-Ying Lai; Albert Vexler
Journal:  J Stat Plan Inference       Date:  2010-07-20       Impact factor: 1.111

9.  The validity of three-class Hotelling trace (3-HT) in describing three-class task performance: comparison of three-class volume under ROC surface (VUS) and 3-HT.

Authors:  Xin He; Eric C Frey
Journal:  IEEE Trans Med Imaging       Date:  2009-02       Impact factor: 10.048

10.  Computer-aided assessment of diagnostic images for epidemiological research.

Authors:  Alison G Abraham; Donald D Duncan; Stephen J Gange; Sheila West
Journal:  BMC Med Res Methodol       Date:  2009-11-11       Impact factor: 4.615

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