Abstract
In this paper, we present the results of experiments identifying the drug treatment relation and drug treatment attributes like dosage, treatment frequency and duration from abstracts of medical publications using linguistic patterns. The approach uses an automatic linguistic pattern construction algorithm after the dataset has been semantically annotated. The automatically constructed patterns were able to identify treatment relations and their attributes with varying success. We observe that the simple (or naïve) treatment patterns performs much better than the non-naïve treatment patterns in identifying sentences with drug treatment relationship in both cancer and non-cancer drug therapy domain. However the drug dosage, frequency and duration patterns performed much better in the identification of relationships in the cancer drug therapy domain than the non-cancer drug therapy domain.
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© 2006 Springer-Verlag Berlin Heidelberg
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Lee, CH., Na, JC., Khoo, C. (2006). Towards Ontology Enrichment with Treatment Relations Extracted from Medical Abstracts. In: Sugimoto, S., Hunter, J., Rauber, A., Morishima, A. (eds) Digital Libraries: Achievements, Challenges and Opportunities. ICADL 2006. Lecture Notes in Computer Science, vol 4312. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11931584_45
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DOI: https://doi.org/10.1007/11931584_45
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-49375-4
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