Analysis of word embeddings and sequence features for clinical information extraction

De Vine, Lance, Kholghi, Mahnoosh, Zuccon, Guido, Sitbon, Laurianne, & Nguyen, Anthony (2015) Analysis of word embeddings and sequence features for clinical information extraction. In 13th Annual Workshop of the Australasian Language Technology Association, 8 - 9 December 2015, University of Western Sydney, Parramatta, NSW.


This study investigates the use of unsupervised features derived from word embedding approaches and novel sequence representation approaches for improving clinical information extraction systems. Our results corroborate previous findings that indicate that the use of word embeddings significantly improve the effectiveness of concept extraction models; however, we further determine the influence that the corpora used to generate such features have. We also demonstrate the promise of sequence-based unsupervised features for further improving concept extraction.

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ID Code: 90401
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Past > Schools > School of Information Systems
Copyright Owner: Copyright 2015 [please consult the authors]
Deposited On: 17 Nov 2015 05:28
Last Modified: 18 Dec 2015 14:56

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