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Can SNOMED CT Changes Be Used as a Surrogate Standard for Evaluating the Performance of Its Auditing Methods?
Guo-Qiang, Zhang; Yan, Huang; Licong, Cui.
Afiliação
  • Guo-Qiang Z; Institute for Biomedical Informatics, University of Kentucky, Lexington, KY.
  • Yan H; Department of Computer Science, University of Kentucky, Lexington, KY.
  • Licong C; Institute for Biomedical Informatics, University of Kentucky, Lexington, KY.
AMIA Annu Symp Proc ; 2017: 1903-1912, 2017.
Article em En | MEDLINE | ID: mdl-29854262
We introduce RGT, Retrospective Ground-Truthing, as a surrogate reference standard for evaluating the performance of automated Ontology Quality Assurance (OQA) methods. The key idea of RGT is to use cumulative SNOMED CT changes derived from its regular longitudinal distributions by the official SNOMED CT editorial board as a partial, surrogate reference standard. The contributions of this paper are twofold: (1) to construct an RGT reference set for SNOMED CT relational changes; and (2) to perform a comparative evaluation of the performances of lattice, non-lattice, and randomized relational error detection methods using the standard precision, recall, and geometric measures. An RGT relational-change reference set of 32,241 IS-A changes were constructed from 5 U.S. editions of SNOMED CT from September 2014 to September 2016, with reversals and changes due to deletion or addition of new concepts excluded. 68,849 independent non-lattice fragments, 118,587 independent lattice fragments, and 446,603 relations were extracted from the SNOMED CT March 2014 distribution. Comparative performance analysis of smaller (less than 15) lattice vs. non-lattice fragments was also given to approach the more realistic setting in which such methods may be applied. Among the 32,241 IS-A changes, independent non-lattice fragments covered 52.8% changes with 26.4% precision with a G-score of 0.373. Even though this G-score is significantly lower in comparison to those in information retrieval, it breaks new ground in that such evaluations have never performed before in the highly discovery-oriented setting of OQA.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Systematized Nomenclature of Medicine / Mineração de Dados Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Systematized Nomenclature of Medicine / Mineração de Dados Idioma: En Ano de publicação: 2017 Tipo de documento: Article