Annotating Clinical Events in Text Snippets for Phenotype Detection

Prescott Klassen, Fei Xia, Lucy Vanderwende, Meliha Yetisgen

Abstract
Early detection and treatment of diseases that onset after a patient is admitted to a hospital, such as pneumonia, is critical to improving and reducing costs in healthcare. NLP systems that analyze the narrative data embedded in clinical artifacts such as x-ray reports can help support early detection. In this paper, we consider the importance of identifying the change of state for events - in particular, clinical events that measure and compare the multiple states of a patient’s health across time. We propose a schema for event annotation comprised of five fields and create preliminary annotation guidelines for annotators to apply the schema. We then train annotators, measure their performance, and finalize our guidelines. With the complete guidelines, we then annotate a corpus of snippets extracted from chest x-ray reports in order to integrate the annotations as a new source of features for classification tasks.
Anthology ID:
L14-1334
Volume:
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
Month:
May
Year:
2014
Address:
Reykjavik, Iceland
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Hrafn Loftsson, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
2753–2757
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/386_Paper.pdf
DOI:
Bibkey:
Cite (ACL):
Prescott Klassen, Fei Xia, Lucy Vanderwende, and Meliha Yetisgen. 2014. Annotating Clinical Events in Text Snippets for Phenotype Detection. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 2753–2757, Reykjavik, Iceland. European Language Resources Association (ELRA).
Cite (Informal):
Annotating Clinical Events in Text Snippets for Phenotype Detection (Klassen et al., LREC 2014)
Copy Citation:
PDF:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/386_Paper.pdf
PDF Search