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      Receiver Operating Characteristic (ROC) Curve: Practical Review for Radiologists

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          Abstract

          The receiver operating characteristic (ROC) curve, which is defined as a plot of test sensitivity as the y coordinate versus its 1-specificity or false positive rate (FPR) as the x coordinate, is an effective method of evaluating the performance of diagnostic tests. The purpose of this article is to provide a nonmathematical introduction to ROC analysis. Important concepts involved in the correct use and interpretation of this analysis, such as smooth and empirical ROC curves, parametric and nonparametric methods, the area under the ROC curve and its 95% confidence interval, the sensitivity at a particular FPR, and the use of a partial area under the ROC curve are discussed. Various considerations concerning the collection of data in radiological ROC studies are briefly discussed. An introduction to the software frequently used for performing ROC analyses is also presented.

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          Most cited references13

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          The meaning and use of the area under a receiver operating characteristic (ROC) curve.

          A representation and interpretation of the area under a receiver operating characteristic (ROC) curve obtained by the "rating" method, or by mathematical predictions based on patient characteristics, is presented. It is shown that in such a setting the area represents the probability that a randomly chosen diseased subject is (correctly) rated or ranked with greater suspicion than a randomly chosen non-diseased subject. Moreover, this probability of a correct ranking is the same quantity that is estimated by the already well-studied nonparametric Wilcoxon statistic. These two relationships are exploited to (a) provide rapid closed-form expressions for the approximate magnitude of the sampling variability, i.e., standard error that one uses to accompany the area under a smoothed ROC curve, (b) guide in determining the size of the sample required to provide a sufficiently reliable estimate of this area, and (c) determine how large sample sizes should be to ensure that one can statistically detect differences in the accuracy of diagnostic techniques.
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            The area above the ordinal dominance graph and the area below the receiver operating characteristic graph

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              ROC methodology in radiologic imaging.

              David Metz (1986)
              If the performance of a diagnostic imaging system is to be evaluated objectively and meaningfully, one must compare radiologists' image-based diagnoses with actual states of disease and health in a way that distinguishes between the inherent diagnostic capacity of the radiologists' interpretations of the images, and any tendencies to "under-read" or "over-read". ROC methodology provides the only known basis for distinguishing between these two aspects of diagnostic performance. After identifying the fundamental issues that motivate ROC analysis, this article develops ROC concepts in an intuitive way. The requirements of a valid ROC study and practical techniques for ROC data collection and data analysis are sketched briefly. A survey of the radiologic literature indicates the broad variety of evaluation studies in which ROC analysis has been employed.
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                Author and article information

                Journal
                Korean J Radiol
                KJR
                Korean Journal of Radiology
                The Korean Radiological Society
                1229-6929
                2005-8330
                Jan-Mar 2004
                31 March 2004
                : 5
                : 1
                : 11-18
                Affiliations
                [1 ]Department of Radiology, Seoul National University College of Medicine and Institute of Radiation Medicine, SNUMRC, Korea.
                [2 ]Biostatistics Section, Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, AR, U.S.A.
                Author notes
                Address reprint requests to: Jin Mo Goo, MD, Department of Radiology, Seoul National University Hospital, 28 Yongon-dong, Chongro-gu, Seoul 110-744, Korea. Tel. (822) 760-2584, Fax. (822) 743-6385, jmgoo@ 123456plaza.snu.ac.kr
                Article
                10.3348/kjr.2004.5.1.11
                2698108
                15064554
                73951b31-e412-4f2f-808b-4606ef349133
                Copyright © 2004 The Korean Radiological Society

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 27 January 2004
                : 05 February 2004
                Categories
                Review

                Radiology & Imaging
                software reviews,statistical analysis,diagnostic radiology,receiver operating characteristic (roc) curve

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