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Automatic tagging of medical reports based on International Classification of Functioning, Disability and Health
Zupanec, Žiga (Author), Šajn, Luka (Author)

URLURL - Presentation file, Visit http://eprints.fri.uni-lj.si/3091/ This link opens in a new window

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

Language:Unknown
Keywords:machine learning, natural language processing, medical report annotation, classification of functioning, disability, ICF, WHO
Work type:Not categorized (r6)
Organization:FRI - Faculty of computer and information science
Year:2011
Views:396
Downloads:134
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