A bottom-up approach to MEDLINE indexing recommendations

Antonio Jimeno-Yepes, Bartlomiej Wilkowski, James/G Mork, Elizabeth Van Lenten, Dina Demner Fushman, Alan/R Aronson

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


    MEDLINE indexing performed by the US National Library of Medicine staff describes the essence of a biomedical publication in about 14 Medical Subject Headings (MeSH). Since 2002, this task is assisted by the Medical Text Indexer (MTI) program. We present a bottom-up approach to MEDLINE indexing in which the abstract is searched for indicators for a specific MeSH recommendation in a two-step process. Supervised machine learning combined with triage rules improves sensitivity of recommendations while keeping the number of recommended terms relatively small. Improvement in recommendations observed in this work warrants further exploration of this approach to MTI recommendations on a larger set of MeSH headings.
    Original languageEnglish
    Title of host publicationAMIA 2011 Proceedings
    Publication date2011
    Publication statusPublished - 2011
    EventAMIA 2011 Annual Symposium - Washington DC, WA, United States
    Duration: 22 Oct 201126 Oct 2011


    ConferenceAMIA 2011 Annual Symposium
    Country/TerritoryUnited States
    CityWashington DC, WA
    Internet address


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