Automatic extraction of relations between medical concepts in clinical texts
نویسندگان
چکیده
منابع مشابه
Automatic extraction of relations between medical concepts in clinical texts
OBJECTIVE A supervised machine learning approach to discover relations between medical problems, treatments, and tests mentioned in electronic medical records. MATERIALS AND METHODS A single support vector machine classifier was used to identify relations between concepts and to assign their semantic type. Several resources such as Wikipedia, WordNet, General Inquirer, and a relation similari...
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BACKGROUND Information extraction is a complex task which is necessary to develop high-precision information retrieval tools. In this paper, we present the platform MeTAE (Medical Texts Annotation and Exploration). MeTAE allows (i) to extract and annotate medical entities and relationships from medical texts and (ii) to explore semantically the produced RDF annotations. RESULTS Our annotation...
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ژورنال
عنوان ژورنال: Journal of the American Medical Informatics Association
سال: 2011
ISSN: 1067-5027,1527-974X
DOI: 10.1136/amiajnl-2011-000153