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    Modelling and extraction of variability in free-text medication prescriptions from an anonymised primary care electronic medical record research database.

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    Authors
    Karystianis, George
    Sheppard, T
    Dixon, W
    Nenadic, G
    Affiliation
    School of Computer Science, University of Manchester, Manchester, UK
    Issue Date
    2016
    
    Metadata
    Show full item record
    Abstract
    Free-text medication prescriptions contain detailed instruction information that is key when preparing drug data for analysis. The objective of this study was to develop a novel model and automated text-mining method to extract detailed structured medication information from free-text prescriptions and explore their variability (e.g. optional dosages) in primary care research databases.
    Citation
    Modelling and extraction of variability in free-text medication prescriptions from an anonymised primary care electronic medical record research database. 2016, 16 (1):18 BMC Med Inform Decis Mak
    Journal
    BMC Medical Informatics and Decision Making
    URI
    http://hdl.handle.net/10541/596628
    DOI
    10.1186/s12911-016-0255-x
    PubMed ID
    26860263
    Type
    Article
    Language
    en
    ISSN
    1472-6947
    ae974a485f413a2113503eed53cd6c53
    10.1186/s12911-016-0255-x
    Scopus Count
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