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Items: 1 to 20 of 151

1.

Translational biomarker discovery in clinical metabolomics: an introductory tutorial.

Xia J, Broadhurst DI, Wilson M, Wishart DS.

Metabolomics. 2013 Apr;9(2):280-299.

2.

Exploring medical diagnostic performance using interactive, multi-parameter sourced receiver operating characteristic scatter plots.

Moore HE 4th, Andlauer O, Simon N, Mignot E.

Comput Biol Med. 2014 Apr;47:120-9. doi: 10.1016/j.compbiomed.2014.01.012.

PMID:
24561350
3.

PanelComposer: a web-based panel construction tool for multivariate analysis of disease biomarker candidates.

Jeong SK, Na K, Kim KY, Kim H, Paik YK.

J Proteome Res. 2012 Dec 7;11(12):6277-81. doi: 10.1021/pr3004387.

PMID:
23140350
4.

Robust estimation of area under ROC curve using auxiliary variables in the presence of missing biomarker values.

Long Q, Zhang X, Johnson BA.

Biometrics. 2011 Jun;67(2):559-67. doi: 10.1111/j.1541-0420.2010.01487.x.

PMID:
20825391
5.

pROC: an open-source package for R and S+ to analyze and compare ROC curves.

Robin X, Turck N, Hainard A, Tiberti N, Lisacek F, Sanchez JC, Müller M.

BMC Bioinformatics. 2011 Mar 17;12:77. doi: 10.1186/1471-2105-12-77.

6.

The partial area under the summary ROC curve.

Walter SD.

Stat Med. 2005 Jul 15;24(13):2025-40.

PMID:
15900606
7.

Metabolomic study for diagnostic model of oesophageal cancer using gas chromatography/mass spectrometry.

Wu H, Xue R, Lu C, Deng C, Liu T, Zeng H, Wang Q, Shen X.

J Chromatogr B Analyt Technol Biomed Life Sci. 2009 Oct 1;877(27):3111-7. doi: 10.1016/j.jchromb.2009.07.039.

PMID:
19716777
8.

A program for computing the prediction probability and the related receiver operating characteristic graph.

Jordan D, Steiner M, Kochs EF, Schneider G.

Anesth Analg. 2010 Dec;111(6):1416-21. doi: 10.1213/ANE.0b013e3181fb919e. Review.

PMID:
21059744
9.

Saliva metabolomics opens door to biomarker discovery, disease diagnosis, and treatment.

Zhang A, Sun H, Wang X.

Appl Biochem Biotechnol. 2012 Nov;168(6):1718-27. doi: 10.1007/s12010-012-9891-5. Review.

PMID:
22971835
10.

Evaluation of qPCR curve analysis methods for reliable biomarker discovery: bias, resolution, precision, and implications.

Ruijter JM, Pfaffl MW, Zhao S, Spiess AN, Boggy G, Blom J, Rutledge RG, Sisti D, Lievens A, De Preter K, Derveaux S, Hellemans J, Vandesompele J.

Methods. 2013 Jan;59(1):32-46. doi: 10.1016/j.ymeth.2012.08.011.

PMID:
22975077
11.

Multi-reader multi-case studies using the area under the receiver operator characteristic curve as a measure of diagnostic accuracy: systematic review with a focus on quality of data reporting.

Dendumrongsup T, Plumb AA, Halligan S, Fanshawe TR, Altman DG, Mallett S.

PLoS One. 2014 Dec 26;9(12):e116018. doi: 10.1371/journal.pone.0116018. Review.

13.

Caveats and pitfalls of ROC analysis in clinical microarray research (and how to avoid them).

Berrar D, Flach P.

Brief Bioinform. 2012 Jan;13(1):83-97. doi: 10.1093/bib/bbr008.

14.

Receiver operating characteristic (ROC) curve for medical researchers.

Kumar R, Indrayan A.

Indian Pediatr. 2011 Apr;48(4):277-87.

PMID:
21532099
15.

A Systematic Strategy for Screening and Application of Specific Biomarkers in Hepatotoxicity Using Metabolomics Combined With ROC Curves and SVMs.

Li Y, Wang L, Ju L, Deng H, Zhang Z, Hou Z, Xie J, Wang Y, Zhang Y.

Toxicol Sci. 2016 Apr;150(2):390-9. doi: 10.1093/toxsci/kfw001.

PMID:
26781514
17.
18.

StAR: a simple tool for the statistical comparison of ROC curves.

Vergara IA, Norambuena T, Ferrada E, Slater AW, Melo F.

BMC Bioinformatics. 2008 Jun 5;9:265. doi: 10.1186/1471-2105-9-265.

19.

Brief critical review: Statistical assessment of biomarker performance.

Kampfrath T, Levinson SS.

Clin Chim Acta. 2013 Apr 18;419:102-7. doi: 10.1016/j.cca.2013.02.006. Review.

PMID:
23428592
20.

A tutorial on the use of ROC analysis for computer-aided diagnostic systems.

Scheipers U, Perrey C, Siebers S, Hansen C, Ermert H.

Ultrason Imaging. 2005 Jul;27(3):181-98. Review.

PMID:
16550707
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