Staggered NLP-assisted refinement for Clinical Annotations of Chronic Disease Events
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.
PDF Abstract LREC 2016 PDF LREC 2016 AbstractTasks
Datasets
Add Datasets
introduced or used in this paper
Results from the Paper
Submit
results from this paper
to get state-of-the-art GitHub badges and help the
community compare results to other papers.
Methods
No methods listed for this paper. Add
relevant methods here
