PubMed · 1994 · 18 citations · 4 references
ComputingBiomedical InformaticsMedical EducationBiomedical Text MiningInformation RetrievalNatural Language ProcessingBiomedical Document RetrievalHealth Information RetrievalInformation ExtractionMedical TerminologyTerminology MappingText MiningBiomedical Information ExtractionBiomedical Information RetrievalBiomedical Text RetrievalElectronic Medical RecordsInformation Extraction From Biomedical TextMedical Document RetrievalPatient Medical RecordsUnified Medical Language System
Recognition of the biomedical concepts in a document is prerequisite to further processing of the document: medical educators examine curricular documents to discover the coverage of certain topics, detect unwanted redundancies, integrate new content, and delete old content; and clinicians are concerned with terms in patient medical records for purposes ranging from creation of an electronic medical record to identification of medical literature relevant to a particular case. POSTDOC (POSTprocessor of DOCuments) is a computer application that (1) accepts as input a free-text, ASCII-formatted document and uses the Unified Medical Language System (UMLS) Metathesaurus to recognize relevant main concept terms; (2) provides term co-occurrence data and thus is able to identify potentially increasing correlations among concepts within the document; and (3) retrieves references from MEDLINE files based on user identification of relevant subjects. This paper describes a formative evaluation of POSTDOC's ability to recognize UMLS Metathesaurus biomedical concepts in medical school lecture outlines. The "precision" and "recall" varied over a wide range and were deemed not yet acceptable for automated creation of a database of concepts from curricular documents. However, results were good enough to warrant further study and continued system development.
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Computer databases of medical school curricula
William D. Mattern, M. Brownell Anderson, Kristin Aune et al. · Academic Medicine · 1992 · 19 citations