Mixtures of receiver operating characteristic curves Journal Article


Author: Gonen, M.
Article Title: Mixtures of receiver operating characteristic curves
Abstract: Rationale and Objectives: Receiver operating characteristic (ROC) curves are ubiquitous in the analysis of imaging metrics as markers ofboth diagnosis and prognosis. While empirical estimation of ROC curves remains the most popular method, there are several reasons to consider smooth estimates based on a parametric model. Materials and Methods: A mixture model is considered for modeling the distribution of the marker in the diseased population motivated by the biological observation that there is more heterogeneity in the diseased population than there is in the normal one. It is shown that this model results in an analytically tractable ROC curve which is itself a mixture of ROC curves. Results: The use of creatine kinase-BB isoenzyme in diagnosis of severe head trauma is used as an example. ROC curves are fit using the direct binormal method, ROCKIT software, and the Box-Cox transformation as well as the proposed mixture model. The mixture model generates an ROC curve that is much closer to the empirical one than the other methods considered. Conclusions: Mixtures of ROC curves can be helpful in fitting smooth ROC curves in datasets where the diseased population has higher variability than can be explained by a single distribution. © 2013 AUR.
Keywords: positron emission tomography; biological markers; diagnostic procedure; computer assisted tomography; algorithms; data interpretation, statistical; cerebrospinal fluid; models, statistical; software; radiodiagnosis; model; roc curve; receiver operating characteristic; roc curves; e-m algorithm; finite mixture; creatine kinase bb; head injury; craniocerebral trauma; creatine kinase, bb form
Journal Title: Academic Radiology
Volume: 20
Issue: 7
ISSN: 1076-6332
Publisher: Elsevier Science, Inc.  
Date Published: 2013-07-01
Start Page: 831
End Page: 837
Language: English
DOI: 10.1016/j.acra.2013.03.003
PROVIDER: scopus
PUBMED: 23643788
PMCID: PMC3928669
DOI/URL:
Notes: --- - Cited By (since 1996):1 - "Export Date: 1 July 2013" - "CODEN: ARADF" - "Source: Scopus"
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  1. Mithat Gonen
    1030 Gonen