Staggered NLP-assisted refinement for Clinical Annotations of Chronic Disease Events

Stephen Wu, Chung-Il Wi, Sunghwan Sohn, Hongfang Liu, Young Juhn


Abstract
Domain-specific annotations for NLP are often centered on real-world applications of text, and incorrect annotations may be particularly unacceptable. In medical text, the process of manual chart review (of a patient’s medical record) is error-prone due to its complexity. We propose a staggered NLP-assisted approach to the refinement of clinical annotations, an interactive process that allows initial human judgments to be verified or falsified by means of comparison with an improving NLP system. We show on our internal Asthma Timelines dataset that this approach improves the quality of the human-produced clinical annotations.
Anthology ID:
L16-1068
Volume:
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
Month:
May
Year:
2016
Address:
Portorož, Slovenia
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
426–429
Language:
URL:
https://aclanthology.org/L16-1068
DOI:
Bibkey:
Cite (ACL):
Stephen Wu, Chung-Il Wi, Sunghwan Sohn, Hongfang Liu, and Young Juhn. 2016. Staggered NLP-assisted refinement for Clinical Annotations of Chronic Disease Events. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 426–429, Portorož, Slovenia. European Language Resources Association (ELRA).
Cite (Informal):
Staggered NLP-assisted refinement for Clinical Annotations of Chronic Disease Events (Wu et al., LREC 2016)
Copy Citation:
PDF:
https://aclanthology.org/L16-1068.pdf