Staggered NLP-assisted refinement for clinical annotations of chronic disease events

Stephen T. Wu, Chung Il Wi, Sunghwan Sohn, Hongfang D Liu, Young J Juhn

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationProceedings of the 10th International Conference on Language Resources and Evaluation, LREC 2016
PublisherEuropean Language Resources Association (ELRA)
Pages426-429
Number of pages4
ISBN (Electronic)9782951740891
StatePublished - Jan 1 2016
Event10th International Conference on Language Resources and Evaluation, LREC 2016 - Portoroz, Slovenia
Duration: May 23 2016May 28 2016

Other

Other10th International Conference on Language Resources and Evaluation, LREC 2016
CountrySlovenia
CityPortoroz
Period5/23/165/28/16

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Keywords

  • Annotation refinement
  • Clinical text
  • Rule-based NLP
  • Staggered approaches

ASJC Scopus subject areas

  • Linguistics and Language
  • Library and Information Sciences
  • Language and Linguistics
  • Education

Cite this

Wu, S. T., Wi, C. I., Sohn, S., Liu, H. D., & Juhn, Y. J. (2016). Staggered NLP-assisted refinement for clinical annotations of chronic disease events. In Proceedings of the 10th International Conference on Language Resources and Evaluation, LREC 2016 (pp. 426-429). European Language Resources Association (ELRA).