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	title        = {Applying MeSH® to the (Swedish) Clinical Domain - Evaluation and Lessons learned},
	abstract     = {Medical discharge summaries and clinical notes provide an information rich, nearly unexplored corpus of evidential knowledge that is considered as a potential goldmine for both medical scientists as well as practitioners in the language technology field. The capability to extract the key concepts and their relationships from such data can be of great value for knowledge management tasks such as indexing, data interchange, data aggregation and clinical decision support. The purpose of this work is to get insights into the feasibility of applying the content of a controlled vocabulary, the Medical Subject Headings (MeSH) to a sample of electronic discharge letters (i.e. free text clinical notes). We explore the application of natural language processing (NLP) techniques to the challenge of efficiently detecting the terminology, as encoded in MeSH and we evaluate MeSH in this setting, showing that a lot of work remains to be done in order to increase the coverage of the resource both in terms of its breadth and depth.
	booktitle    = {Proceedings of the 6th Scandinavian Health Informatics and the 12th Swedish National Term Conference},
	author       = {Kokkinakis, Dimitrios and Thurin, Anders},
	year         = {2008},