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Automatic tagging of medical reports based on International Classification of Functioning, Disability and Health

žiga zupanec and Luka Šajn (2011) Automatic tagging of medical reports based on International Classification of Functioning, Disability and Health. unpublished . (Unpublished)

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    Abstract

    Patients coming from different countries bring their medical reports with them and sometimes doctors do not understand the content in full. World health organization provided a framework for measuring health and disability at both individual and population levels named ”International Classification of Functioning, Disability and Health” (ICF). ICF is focusing on unifying framework for classifying health components of functioning and disability and thus enabling data comparison between countries. The paper presents an automated procedure for tagging medical reports with the belonging ICF classes. Our final result will present a webpage service that will allow physicians to upload documents describing the patient’s status. The service will provide a list of most probable tags listed in the ICF classification. Matching is supported by methods such as parsing, eliminating stop words, lemmatization and stemming of word

    Item Type: Article
    Keywords: machine learning, natural language processing, medical report annotation, classification of functioning, disability, ICF, WHO
    Institution: University of Ljubljana
    Department: Faculty of Computer and Information Science
    Divisions: Faculty of Computer and Information Science > Computer Vision Laboratory
    Item ID: 3091
    Date Deposited: 14 Sep 2015 14:56
    Last Modified: 14 Sep 2015 14:56
    URI: http://eprints.fri.uni-lj.si/id/eprint/3091

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