upload hub_repos/n2c2_2009/README.md to hub from bigbio repo

README.md

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+
+---
+language: 
+- en
+license: other
+license_bigbio_shortname: DUA
+pretty_name: n2c2 2009 Medications
+---
+
+
+# Dataset Card for n2c2 2009 Medications
+
+## Dataset Description
+
+- **Homepage:** https://portal.dbmi.hms.harvard.edu/projects/n2c2-nlp/
+- **Pubmed:** True
+- **Public:** False
+- **Tasks:** Named Entity Recognition
+
+
+The Third i2b2 Workshop on Natural Language Processing Challenges for Clinical Records
+focused on the identification of medications, their dosages, modes (routes) of administration,
+frequencies, durations, and reasons for administration in discharge summaries.
+The third i2b2 challenge—that is, the medication challenge—extends information
+extraction to relation extraction; it requires extraction of medications and
+medication-related information followed by determination of which medication
+belongs to which medication-related details.
+
+The medication challenge was designed as an information extraction task.
+The goal, for each discharge summary, was to extract the following information
+on medications experienced by the patient:
+1. Medications (m): including names, brand names, generics, and collective names of prescription substances,
+over the counter medications, and other biological substances for which the patient is the experiencer.
+2. Dosages (do): indicating the amount of a medication used in each administration.
+3. Modes (mo): indicating the route for administering the medication.
+4. Frequencies (f): indicating how often each dose of the medication should be taken.
+5. Durations (du): indicating how long the medication is to be administered.
+6. Reasons (r): stating the medical reason for which the medication is given.
+7. Certainty (c): stating whether the event occurs. Certainty can be expressed by uncertainty words,
+e.g., “suggested”, or via modals, e.g., “should” indicates suggestion.
+8. Event (e): stating on whether the medication is started, stopped, or continued.
+9. Temporal (t): stating whether the medication was administered in the past,
+is being administered currently, or will be administered in the future, to the extent
+that this information is expressed in the tense of the verbs and auxiliary verbs used to express events.
+10. List/narrative (ln): indicating whether the medication information appears in a
+list structure or in narrative running text in the discharge summary.
+
+The medication challenge asked that systems extract the text corresponding to each of the fields
+for each of the mentions of the medications that were experienced by the patients.
+
+The values for the set of fields related to a medication mention, if presented within a
+two-line window of the mention, were linked in order to create what we defined as an ‘entry’.
+If the value of a field for a mention were not specified within a two-line window,
+then the value ‘nm’ for ‘not mentioned’ was entered and the offsets were left unspecified.
+
+Since the dataset annotations were crowd-sourced, it contains various violations that are handled
+throughout the data loader via means of exception catching or conditional statements. e.g.
+annotation: anticoagulation, while in text all words are to be separated by space which
+means words at end of sentence will always contain `.` and hence won't be an exact match
+i.e. `anticoagulation` != `anticoagulation.` from doc_id: 818404
+
+
+
+## Citation Information
+
+```
+@article{DBLP:journals/jamia/UzunerSC10,
+  author    = {
+                Ozlem Uzuner and
+                Imre Solti and
+                Eithon Cadag
+               },
+  title     = {Extracting medication information from clinical text},
+  journal   = {J. Am. Medical Informatics Assoc.},
+  volume    = {17},
+  number    = {5},
+  pages     = {514--518},
+  year      = {2010},
+  url       = {https://doi.org/10.1136/jamia.2010.003947},
+  doi       = {10.1136/jamia.2010.003947},
+  timestamp = {Mon, 11 May 2020 22:59:55 +0200},
+  biburl    = {https://dblp.org/rec/journals/jamia/UzunerSC10.bib},
+  bibsource = {dblp computer science bibliography, https://dblp.org}
+}
+
+```