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	title        = {Medication Extraction and Guessing in Swedish, French and English. },
	abstract     = {Extraction of information related to the medication is an im-portant task within the biomedical area. While the elaboration and updating of the drug vocabularies cannot follow the rap-id evolution of the drug development, we propose an automat-ic method for the extraction of known and new drug names. Our method combines internal and contextual clues. The method is applied to different types of documents in three languages (Swedish, French and English). The results indi-cate that with this kind of approach, we can efficiently update and enrich the existing drug vocabularies (probably with rap-id manual browsing). Precision and recall scores varied be-tween 81%-91% for precision and 85%-100% for recall. As a future work we intend to continuously refine the approach, by for instance better integration of semantic patterns and fuzzy matching that should hopefully enable further increase of the obtained results.},
	booktitle    = {Proceedings of the 14th World Congress on Medical and Health Informatics (MEDINFO). Studies in Health Technology and Informatics. Copenhagen, Denmark.},
	author       = {Hamon, Thierry and Grabar, Natalia and Kokkinakis, Dimitrios},
	year         = {2013},
	volume       = {192},