Annotation of pain and anesthesia events for surgery-related processes and outcomes extraction

Wen-wai Yim, Dario Tedesco, Catherine Curtin, Tina Hernandez-Boussard


Abstract
Pain and anesthesia information are crucial elements to identifying surgery-related processes and outcomes. However pain is not consistently recorded in the electronic medical record. Even when recorded, the rich complex granularity of the pain experience may be lost. Similarly, anesthesia information is recorded using local electronic collection systems; though the accuracy and completeness of the information is unknown. We propose an annotation schema to capture pain, pain management, and anesthesia event information.
Anthology ID:
W17-2325
Volume:
BioNLP 2017
Month:
August
Year:
2017
Address:
Vancouver, Canada,
Venues:
BioNLP | WS
SIG:
SIGBIOMED
Publisher:
Association for Computational Linguistics
Note:
Pages:
200–205
Language:
URL:
https://www.aclweb.org/anthology/W17-2325
DOI:
10.18653/v1/W17-2325
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/W17-2325.pdf