Literature DB >> 15684123

Agreement, the f-measure, and reliability in information retrieval.

George Hripcsak1, Adam S Rothschild.   

Abstract

Information retrieval studies that involve searching the Internet or marking phrases usually lack a well-defined number of negative cases. This prevents the use of traditional interrater reliability metrics like the kappa statistic to assess the quality of expert-generated gold standards. Such studies often quantify system performance as precision, recall, and F-measure, or as agreement. It can be shown that the average F-measure among pairs of experts is numerically identical to the average positive specific agreement among experts and that kappa approaches these measures as the number of negative cases grows large. Positive specific agreement-or the equivalent F-measure-may be an appropriate way to quantify interrater reliability and therefore to assess the reliability of a gold standard in these studies.

Mesh:

Year:  2005        PMID: 15684123      PMCID: PMC1090460          DOI: 10.1197/jamia.M1733

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  4 in total

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Authors:  George Hripcsak; Adam Wilcox
Journal:  J Am Med Inform Assoc       Date:  2002 Jan-Feb       Impact factor: 4.497

2.  Measuring agreement between two judges on the presence or absence of a trait.

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Journal:  Biometrics       Date:  1975-09       Impact factor: 2.571

Review 3.  Measuring agreement in medical informatics reliability studies.

Authors:  George Hripcsak; Daniel F Heitjan
Journal:  J Biomed Inform       Date:  2002-04       Impact factor: 6.317

4.  Approximate standard errors and confidence intervals for indices of positive and negative agreement.

Authors:  P Graham; B Bull
Journal:  J Clin Epidemiol       Date:  1998-09       Impact factor: 6.437

  4 in total
  167 in total

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Journal:  AMIA Annu Symp Proc       Date:  2005

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Journal:  J Am Med Inform Assoc       Date:  2019-11-01       Impact factor: 4.497

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