Rethinking information delivery: using a natural language processing application for point-of-care data discovery.

Objective: This paper examines the use of Semantic MEDLINE, a natural language processing application enhanced with a statistical algorithm known as Combo, as a potential decision support tool for clinicians. Semantic MEDLINE summarizes text in PubMed citations, transforming it into compact declarat...

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Publicado en:Journal of the Medical Library Association Vol. 100; no. 2; pp. 113 - 121
Autores principales: Workman, T. Elizabeth, Stoddart, Joan M.
Formato: pictorial research tables/charts Journal Article
Publicado: University of Pittsburgh, University Library System Apr2012
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Rethinking information delivery: using a natural language processing application for point-of-care data discovery.
      aug:
        au:
          Workman, T. Elizabeth
          Stoddart, Joan M.
        affil: Postdoctoral Research Associate, Department of Biomedical Informatics, University of Utah, HSEB 5775, 26 South 2000 East, Salt Lake City, UT 84112
      sug:
        subj:
          Semantics
          Medline
          Computerized Literature Searching
          Natural Language Processing
          Information Retrieval Methods
          Human
          Funding Source
          Algorithms
          Decision Support Systems, Clinical
          Information Needs
          Resource Databases, Health
          Programming Languages
          Website Development
      ab: Objective: This paper examines the use of Semantic MEDLINE, a natural language processing application enhanced with a statistical algorithm known as Combo, as a potential decision support tool for clinicians. Semantic MEDLINE summarizes text in PubMed citations, transforming it into compact declarations that are filtered according to a user's information need that can be displayed in a graphic interface. Integration of the Combo algorithm enables Semantic MEDLINE to deliver information salient to many diverse needs. Methods: The authors selected three disease topics and crafted PubMed search queries to retrieve citations addressing the prevention of these diseases. They then processed the citations with Semantic MEDLINE, with the Combo algorithm enhancement. To evaluate the results, they constructed a reference standard for each disease topic consisting of preventive interventions recommended by a commercial decision support tool. Results: Semantic MEDLINE with Combo produced an average recall of 79% in primary and secondary analyses, an average precision of 45%, and a final average F-score of 0.57. Conclusion: This new approach to point-of-care information delivery holds promise as a decision support tool for clinicians. Health sciences libraries could implement such technologies to deliver tailored information to their users.
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    language: English
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