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,
- Editors:
- Kevin Bretonnel Cohen, Dina Demner-Fushman, Sophia Ananiadou, Junichi Tsujii
- Venue:
- BioNLP
- SIG:
- SIGBIOMED
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 200–205
- Language:
- URL:
- https://aclanthology.org/W17-2325
- DOI:
- 10.18653/v1/W17-2325
- Cite (ACL):
- Wen-wai Yim, Dario Tedesco, Catherine Curtin, and Tina Hernandez-Boussard. 2017. Annotation of pain and anesthesia events for surgery-related processes and outcomes extraction. In BioNLP 2017, pages 200–205, Vancouver, Canada,. Association for Computational Linguistics.
- Cite (Informal):
- Annotation of pain and anesthesia events for surgery-related processes and outcomes extraction (Yim et al., BioNLP 2017)
- PDF:
- https://preview.aclanthology.org/bionlp-24-ingestion/W17-2325.pdf