Literature DB >> 9917023

Three-way ROCs.

D Mossman1.   

Abstract

Receiver operating characteristic (ROC) analysis traditionally has dealt with dichotomous diagnostic tasks (e.g., determining whether a disorder is present or absent). Often, however, medical problems involve distinguishing among more than two diagnostic alternatives. This article extends ROC concepts to diagnostic enterprises with three possible outcomes. For a trichotomous decision task, one can plot a ROC surface on three-dimensional coordinates; the volume under the ROC surface (VUS) equals the probability that test values will allow a decision maker to correctly sort a trio of items containing a randomly-selected member from each of three populations. Thus, the VUS summarizes global diagnostic accuracy for trichotomous tests, just as the area under a ROC curve does for a two-alternative diagnostic task. Information gain at points on the surface can be calculated just as is done for two-dimensional ROC curves, and investigators can thus compare three-way ROCs by comparing maximum information gain on each ROC surface.

Mesh:

Year:  1999        PMID: 9917023     DOI: 10.1177/0272989X9901900110

Source DB:  PubMed          Journal:  Med Decis Making        ISSN: 0272-989X            Impact factor:   2.583


  44 in total

1.  Ideal observers and optimal ROC hypersurfaces in N-class classification.

Authors:  Darrin C Edwards; Charles E Metz; Matthew A Kupinski
Journal:  IEEE Trans Med Imaging       Date:  2004-07       Impact factor: 10.048

2.  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

3.  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

4.  Duplex microsphere-based immunoassay for detection of anti-West Nile virus and anti-St. Louis encephalitis virus immunoglobulin m antibodies.

Authors:  Alison J Johnson; Amanda J Noga; Olga Kosoy; Robert S Lanciotti; Alicia A Johnson; Brad J Biggerstaff
Journal:  Clin Diagn Lab Immunol       Date:  2005-05

5.  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

6.  The meaning of the opposition between the healthy and the pathological and its consequences.

Authors:  Maël Lemoine
Journal:  Med Health Care Philos       Date:  2008-07-30

7.  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

8.  Evaluation of computer-aided detection and diagnosis systems.

Authors:  Nicholas Petrick; Berkman Sahiner; Samuel G Armato; Alberto Bert; Loredana Correale; Silvia Delsanto; Matthew T Freedman; David Fryd; David Gur; Lubomir Hadjiiski; Zhimin Huo; Yulei Jiang; Lia Morra; Sophie Paquerault; Vikas Raykar; Frank Samuelson; Ronald M Summers; Georgia Tourassi; Hiroyuki Yoshida; Bin Zheng; Chuan Zhou; Heang-Ping Chan
Journal:  Med Phys       Date:  2013-08       Impact factor: 4.071

9.  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

10.  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

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