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Shallow semantic parsing of randomized controlled trial reports.

Author information

1
Center for Medical Informatics, Yale University School of Medicine, New Haven, USA.

Abstract

In this work, we are measuring the performance of Propbank-based Machine Learning (ML) for automatically annotating abstracts of Randomized Controlled Trials (CTRs) with semantically meaningful tags. Propbank is a resource of annotated sentences from the Wall Street Journal (WSJ) corpus, and we were interested in assessing performance issues when porting this resource to the medical domain. We compare intra-domain (WSJ/WSJ) with cross-domain (WSJ/medical abstract) performance. Although the intra-domain performance is superior, we found a reasonable cross-domain performance.

PMID:
17238412
PMCID:
PMC1839261
[Indexed for MEDLINE]
Free PMC Article

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