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2009 IEEE International Workshop on Machine Learning for Signal Processing, 2009
In classification problems, major methods focus on the minimization of the classification error rate. This is not always a suitable performance measure when sample numbers of classes are biased. In this case, the area under the Receiver Operating Characteristic curve (AUC) is an effective performance measure.
Shinto Eguchi, Takashi Takenouchi
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In classification problems, major methods focus on the minimization of the classification error rate. This is not always a suitable performance measure when sample numbers of classes are biased. In this case, the area under the Receiver Operating Characteristic curve (AUC) is an effective performance measure.
Shinto Eguchi, Takashi Takenouchi
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ROC Curves for Classification Trees
Medical Decision Making, 1994A common problem in medical diagnosis is to combine information from several tests or patient characteristics into a decision rule to distinguish diseased from healthy patients. Among the statistical procedures proposed to solve this problem, recursive partitioning is appealing for the easily-used and intuitive nature of the rules it produces.
Peter G. Szilagyi +3 more
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Medical Decision Making, 2000
The authors present a method to combine several independent studies of the same (continuous or semiquantitative) diagnostic test, where each study reports a complete ROC curve; a plot of the true-positive rate or sensitivity against the false-positive rate or one minus the specificity.
Arnold D. M. Kester, Frank Buntinx
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The authors present a method to combine several independent studies of the same (continuous or semiquantitative) diagnostic test, where each study reports a complete ROC curve; a plot of the true-positive rate or sensitivity against the false-positive rate or one minus the specificity.
Arnold D. M. Kester, Frank Buntinx
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Estimation of a convex ROC curve
Statistics & Probability Letters, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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ROC Curves with Multiple Marker Measurements [PDF]
Biometrics, 1995 Properties of receiver operating characteristic (ROC) curves are explored for markers that are measured repeatedly, through space or time, for each subject. The true underlying response, positive or negative, of each subject is assumed to be constant across marker measurements, and is determined from assessment of some "gold standard." A marker-based ...
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Analyzing a Portion of the ROC Curve
Medical Decision Making, 1989The area under the ROC curve is a common index summarizing the information contained in the curve. When comparing two ROC curves, though, problems arise when interest does not lie in the entire range of false-positive rates (and hence the entire area).
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On the Shape of the Population ROC Curve
Academic Radiology, 2013Human observers often do not produce empirical operating points near the northeast corner of the receiver operating characteristic (ROC) plot, and thus the local shape of the population ROC curve is unknown.We call attention to occult abnormalities and propose that considerations by human observers of the prior probability of occult abnormalities can ...
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Confidence bands for ROC curves
Journal of Statistical Planning and Inference, 2008We develop two methods to construct confidence bands for the receiver operating characteristic (ROC) curve without estimating the densities of the underlying distributions. The first method is based on the smoothed bootstrap while the second method uses the Bonferroni inequality.
Horváth, L., Horváth, Z., Zhou, W.
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Bayesian bootstrap estimation of ROC curve
Statistics in Medicine, 2008AbstractReceiver operating characteristic (ROC) curve is widely applied in measuring discriminatory ability of diagnostic or prognostic tests. This makes the ROC analysis one of the most active research areas in medical statistics. Many parametric and semiparametric estimation methods have been proposed for estimating the ROC curve and its functionals.
Subhashis Ghosal +2 more
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Regional confidence bands for ROC curves
Statistics in Medicine, 2000The performance of a diagnostic test is characterised by its specificity and sensitivity. For a quantitative diagnostic test these criteria depend on the selected cut-off point. The receiver operating characteristic (ROC) curve of a quantitative diagnostic test is generated by plotting sensitivity against specificity as the cut-off point runs through ...
Helmut Schäfer +3 more
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