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upload hub_repos/n2c2_2010/README.md to hub from bigbio repo
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README.md
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---
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language:
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- en
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license: other
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license_bigbio_shortname: DUA
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pretty_name: n2c2 2010 Concepts, Assertions, and Relations
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---
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# Dataset Card for n2c2 2010 Concepts, Assertions, and Relations
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## Dataset Description
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- **Homepage:** https://portal.dbmi.hms.harvard.edu/projects/n2c2-nlp/
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- **Pubmed:** False
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- **Public:** False
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- **Tasks:** Named Entity Recognition, Relation Extraction
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The i2b2/VA corpus contained de-identified discharge summaries from Beth Israel
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Deaconess Medical Center, Partners Healthcare, and University of Pittsburgh Medical
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Center (UPMC). In addition, UPMC contributed de-identified progress notes to the
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i2b2/VA corpus. This dataset contains the records from Beth Israel and Partners.
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The 2010 i2b2/VA Workshop on Natural Language Processing Challenges for Clinical Records comprises three tasks:
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1) a concept extraction task focused on the extraction of medical concepts from patient reports;
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2) an assertion classification task focused on assigning assertion types for medical problem concepts;
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3) a relation classification task focused on assigning relation types that hold between medical problems,
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tests, and treatments.
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i2b2 and the VA provided an annotated reference standard corpus for the three tasks.
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Using this reference standard, 22 systems were developed for concept extraction,
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21 for assertion classification, and 16 for relation classification.
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## Citation Information
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```
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@article{DBLP:journals/jamia/UzunerSSD11,
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author = {
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Ozlem Uzuner and
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Brett R. South and
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Shuying Shen and
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Scott L. DuVall
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},
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title = {2010 i2b2/VA challenge on concepts, assertions, and relations in clinical
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text},
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journal = {J. Am. Medical Informatics Assoc.},
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volume = {18},
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number = {5},
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pages = {552--556},
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year = {2011},
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url = {https://doi.org/10.1136/amiajnl-2011-000203},
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doi = {10.1136/amiajnl-2011-000203},
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timestamp = {Mon, 11 May 2020 23:00:20 +0200},
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biburl = {https://dblp.org/rec/journals/jamia/UzunerSSD11.bib},
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bibsource = {dblp computer science bibliography, https://dblp.org}
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}
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```
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