Literature DB >> 11059479

Determining the area under the ROC curve for a binary diagnostic test.

S B Cantor1, M W Kattan.   

Abstract

The authors provide a simple calculation for the unbiased estimation of the area under the ROC curve for a binary diagnostic test or a continuously valued test result that is effectively used in a binary way. The formula described can be used to interpret the discriminative ability of a diagnostic test.

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Year:  2000        PMID： 11059479     DOI： 10.1177/0272989X0002000410

Source DB:  PubMed          Journal:  Med Decis Making        ISSN： 0272-989X            Impact factor:   2.583


  37 in total

1.  The development and validation of a screening instrument to identify hospitalized medical patients in need of early functional rehabilitation assessment.

Authors:  Carla Boutin Foster; Delia Gorga; Carolyn Padial; Ann Marie Feretti; Debra Berenson; Robin Kline; Rhonda Belue; Mary E Charlson
Journal:  Qual Life Res       Date:  2004-08       Impact factor: 4.147

2.  A Method for the Minimization of Competition Bias in Signal Detection from Spontaneous Reporting Databases.

Authors:  Mickael Arnaud; Francesco Salvo; Ismaïl Ahmed; Philip Robinson; Nicholas Moore; Bernard Bégaud; Pascale Tubert-Bitter; Antoine Pariente
Journal:  Drug Saf       Date:  2016-03       Impact factor: 5.606

3.  Optimizing A syndromic surveillance text classifier for influenza-like illness: Does document source matter?

Authors:  Brett R South; Brett Ray South; Wendy W Chapman; Wendy Chapman; Sylvain Delisle; Shuying Shen; Ericka Kalp; Trish Perl; Matthew H Samore; Adi V Gundlapalli
Journal:  AMIA Annu Symp Proc       Date:  2008-11-06

4.  Empirical performance of a new user cohort method: lessons for developing a risk identification and analysis system.

Authors:  Patrick B Ryan; Martijn J Schuemie; Susan Gruber; Ivan Zorych; David Madigan
Journal:  Drug Saf       Date:  2013-10       Impact factor: 5.606

5.  Replication of the OMOP experiment in Europe: evaluating methods for risk identification in electronic health record databases.

Authors:  Martijn J Schuemie; Rosa Gini; Preciosa M Coloma; Huub Straatman; Ron M C Herings; Lars Pedersen; Francesco Innocenti; Giampiero Mazzaglia; Gino Picelli; Johan van der Lei; Miriam C J M Sturkenboom
Journal:  Drug Saf       Date:  2013-10       Impact factor: 5.606

6.  Alternative outcome definitions and their effect on the performance of methods for observational outcome studies.

Authors:  Christian G Reich; Patrick B Ryan; Martijn J Schuemie
Journal:  Drug Saf       Date:  2013-10       Impact factor: 5.606

7.  Empirical performance of a self-controlled cohort method: lessons for developing a risk identification and analysis system.

Authors:  Patrick B Ryan; Martijn J Schuemie; David Madigan
Journal:  Drug Saf       Date:  2013-10       Impact factor: 5.606

8.  Empirical performance of LGPS and LEOPARD: lessons for developing a risk identification and analysis system.

Authors:  Martijn J Schuemie; David Madigan; Patrick B Ryan
Journal:  Drug Saf       Date:  2013-10       Impact factor: 5.606

9.  The impact of drug and outcome prevalence on the feasibility and performance of analytical methods for a risk identification and analysis system.

Authors:  Christian G Reich; Patrick B Ryan; Marc A Suchard
Journal:  Drug Saf       Date:  2013-10       Impact factor: 5.606

10.  Measuring clinically significant chemotherapy-related toxicities using Medicare claims from Cancer and Leukemia Group B (CALGB) trial participants.

Authors:  Elizabeth B Lamont; James E Herndon; Jane C Weeks; I Craig Henderson; Rogerio Lilenbaum; Richard L Schilsky; Nicholas A Christakis
Journal:  Med Care       Date:  2008-03       Impact factor: 2.983
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