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--- |
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language: |
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- en |
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bigbio_language: |
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- English |
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license: other |
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multilinguality: monolingual |
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bigbio_license_shortname: DUA |
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pretty_name: n2c2 2008 Obesity |
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homepage: https://portal.dbmi.hms.harvard.edu/projects/n2c2-nlp/ |
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bigbio_pubmed: True |
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bigbio_public: False |
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bigbio_tasks: |
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- TEXT_CLASSIFICATION |
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--- |
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# Dataset Card for n2c2 2008 Obesity |
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|
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## Dataset Description |
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|
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- **Homepage:** https://portal.dbmi.hms.harvard.edu/projects/n2c2-nlp/ |
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- **Pubmed:** True |
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- **Public:** False |
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- **Tasks:** TXTCLASS |
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The data for the n2c2 2008 obesity challenge consisted of discharge summaries from |
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the Partners HealthCare Research Patient Data Repository. These data were chosen |
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from the discharge summaries of patients who were overweight or diabetic and had |
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been hospitalized for obesity or diabetes sometime since 12/1/04. De-identification |
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was performed semi-automatically. All private health information was replaced with |
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synthetic identifiers. |
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|
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The data for the challenge were annotated by two obesity experts from the |
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Massachusetts General Hospital Weight Center. The experts were given a textual task, |
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which asked them to classify each disease (see list of diseases above) as Present, |
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Absent, Questionable, or Unmentioned based on explicitly documented information in |
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the discharge summaries, e.g., the statement “the patient is obese”. The experts were |
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also given an intuitive task, which asked them to classify each disease as Present, |
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Absent, or Questionable by applying their intuition and judgment to information in |
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the discharge summaries. |
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## Citation Information |
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|
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``` |
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@article{uzuner2009recognizing, |
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author = { |
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Uzuner, Ozlem |
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}, |
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title = {Recognizing Obesity and Comorbidities in Sparse Data}, |
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journal = {Journal of the American Medical Informatics Association}, |
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volume = {16}, |
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number = {4}, |
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pages = {561-570}, |
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year = {2009}, |
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month = {07}, |
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url = {https://doi.org/10.1197/jamia.M3115}, |
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doi = {10.1197/jamia.M3115}, |
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eprint = {https://academic.oup.com/jamia/article-pdf/16/4/561/2302602/16-4-561.pdf} |
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} |
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|
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``` |
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|
