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Table representation of search results timeline featuring number of search results per year.

Year Number of Results
1978 1
1979 1
1987 16
1988 72
1989 98
1990 138
1991 153
1992 198
1993 178
1994 310
1995 375
1996 409
1997 494
1998 546
1999 554
2000 694
2001 758
2002 830
2003 975
2004 1032
2005 1385
2006 1590
2007 1888
2008 2308
2009 2683
2010 3076
2011 3652
2012 4363
2013 4693
2014 4947
2015 5530
2016 5920
2017 6196
2018 5544
2019 2898
2020 44
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55,974 results
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Page 1
On the use of partial area under the ROC curve for comparison of two diagnostic tests.
Ma H, et al. Biom J 2015. PMID 25537143
Evaluation of diagnostic performance is typically based on the receiver operating characteristic (ROC) curve and the area under the curve (AUC) as its summary index. ...We demonstrated that outside of the classic model there are practically reasonable ROC types for which comparisons of noncrossing concave curves would be more powerful when based on a part of the curve rather than the entire curve. ...
Evaluation of diagnostic performance is typically based on the receiver operating characteristic (ROC) curve and the area unde …
Analyzing a portion of the ROC curve.
McClish DK. Med Decis Making 1989. PMID 2668680
The 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). Numerical integration is suggested for evaluating the area under a portion of the ROC curve. Variance estimates are derived. ...
The area under the ROC curve is a common index summarizing the information contained in the curve. When comparing two …
Precrec: fast and accurate precision-recall and ROC curve calculations in R.
Saito T and Rehmsmeier M. Bioinformatics 2017. PMID 27591081 Free PMC article.
The precision-recall plot is more informative than the ROC plot when evaluating classifiers on imbalanced datasets, but fast and accurate curve calculation tools for precision-recall plots are currently not available. ...
The precision-recall plot is more informative than the ROC plot when evaluating classifiers on imbalanced datasets, but fast and accu …
ROC-kurver og diagnostiske tester
Lydersen S. Tidsskr Nor Laegeforen 2018. PMID 30277050 Norwegian. Free article.
ROC Curves for the Statistical Analysis of Microarray Data.
Cao R and López-de-Ullibarri I. Methods Mol Biol 2019 - Review. PMID 31115892
A receiver operating characteristic (ROC) curve is a graphical plot that illustrates the diagnostic ability of a binary classifier as a function of its discrimination threshold. This chapter is an overview on the use of ROC curves for microarray data. The notion of ROC curve and its motivation is introduced in Subheading 1. ...
A receiver operating characteristic (ROC) curve is a graphical plot that illustrates the diagnostic ability of a binary classi …
Dynamic thresholds and a summary ROC curve: Assessing prognostic accuracy of longitudinal markers.
Saha-Chaudhuri P and Heagerty PJ. Stat Med 2018. PMID 29671890
To characterize the overall accuracy of a time-dependent marker, we introduce a summary ROC curve that displays the overall sensitivity associated with a time-dependent threshold that controls time-varying specificity. ...The proposed summary ROC curve is a natural averaging of time-dependent incident/dynamic ROC curves and therefore provides a single summary of net error rates that can be achieved in the longitudinal setting....
To characterize the overall accuracy of a time-dependent marker, we introduce a summary ROC curve that displays the overall se …
55,974 results
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