Information-theoretic classification of SNOMED improves the organization of context-sensitive excerpts from Cochrane reviews.

Lee Sam, Tara Borlawsky, Ying Tao, Jianrong Li, Carol Friedman, Barry Smith, Yves A Lussier

Research output: Contribution to journalArticle

Abstract

The emphasis on evidence based medicine (EBM) has placed increased focus on finding timely answers to clinical questions in presence of patients. Using a combination of natural language processing for the generation of clinical excerpts and information theoretic distance based clustering, we evaluated multiple approaches for the efficient presentation of context-sensitive EBM excerpts.

Original languageEnglish (US)
Pages (from-to)1100
Number of pages1
JournalAMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
StatePublished - 2007
Externally publishedYes

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Systematized Nomenclature of Medicine
Evidence-Based Medicine
Natural Language Processing
Cluster Analysis

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Information-theoretic classification of SNOMED improves the organization of context-sensitive excerpts from Cochrane reviews. / Sam, Lee; Borlawsky, Tara; Tao, Ying; Li, Jianrong; Friedman, Carol; Smith, Barry; Lussier, Yves A.

In: AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium, 2007, p. 1100.

Research output: Contribution to journalArticle

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AU - Smith, Barry

AU - Lussier, Yves A

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