A bottom-up approach to MEDLINE indexing recommendations

Publication: Research - peer-reviewArticle in proceedings – Annual report year: 2011

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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
StatePublished

Conference

ConferenceAMIA 2011 Annual Symposium
CountryUnited States
CityWashington DC, WA
Period22/10/1126/10/11
Internet addresshttp://www.amia.org/amia2011
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