Building gold standard corpora for medical natural language processing tasks.
We present the construction of three annotated corpora to serve as gold standards for medical natural language processing (NLP) tasks. Clinical notes from the medical record, clinical trial announcements, and FDA drug labels are annotated. We report high inter-annotator agreements (overall F-measures between 0.8467 and 0.9176) for the annotation of Personal Health Information (PHI) elements for a de-identification task and of medications, diseases/disorders, and signs/symptoms for information extraction (IE) task. The annotated corpora of clinical trials and FDA labels will be publicly released and to facilitate translational NLP tasks that require cross-corpora interoperability (e.g. clinical trial eligibility screening) their annotation schemas are aligned with a large scale, NIH-funded clinical text annotation project.
Duke Scholars
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- United States Food and Drug Administration
- United States
- Software
- Natural Language Processing
- Medical Records
- Drug Labeling
- Clinical Trials as Topic
Citation
Published In
EISSN
Publication Date
Volume
Start / End Page
Location
Related Subject Headings
- United States Food and Drug Administration
- United States
- Software
- Natural Language Processing
- Medical Records
- Drug Labeling
- Clinical Trials as Topic