title: Creation of a new longitudinal corpus of clinical narratives.
abstract: The 2014 i2b2/UTHealth Natural Language Processing (NLP) shared task featured a new longitudinal corpus of 1304 records representing 296 diabetic patients. The corpus contains three cohorts: patients who have a diagnosis of coronary artery disease (CAD) in their first record, and continue to have it in subsequent records; patients who do not have a diagnosis of CAD in the first record, but develop it by the last record; patients who do not have a diagnosis of CAD in any record. This paper details the process used to select records for this corpus and provides an overview of novel research uses for this corpus. This corpus is the only annotated corpus of longitudinal clinical narratives currently available for research to the general research community.
authors.affiliation: Dartmouth-Hitchcock Medical Center, Division of Cardiology, Lebanon, NH, USA.
authors.forename: Vishesh
authors.initials: V
authors.lastname: Kumar
authors.affiliation: School of Library and Information Science, Simmons College, Boston, MA, USA. Electronic address: stubbs@simmons.edu.
authors.forename: Amber
authors.initials: A
authors.lastname: Stubbs
authors.affiliation: Harvard Medical School, Boston, MA 02115, USA; Center for Systems Biology, Massachusetts General Hospital, Boston, MA 02114, USA.
authors.forename: Stanley
authors.initials: S
authors.lastname: Shaw
authors.affiliation: Department of Information Studies, State University of New York at Albany, Albany, NY, USA.
authors.forename: Özlem
authors.initials: Ö
authors.lastname: Uzuner
mesh_terms: D000368:Aged; D001900:Boston / Q000453:epidemiology; D015331:Cohort Studies; D015897:Comorbidity; D016494:Computer Security; D003219:Confidentiality; D003324:Coronary Artery Disease / Q000175:diagnosis / Q000453:epidemiology*; D057225:Data Mining / Q000379:methods*; D048909:Diabetes Complications / Q000175:diagnosis / Q000453:epidemiology*; D057286:Electronic Health Records / Q000458:organization & administration*; D005260:Female; D006801:Humans; D015994:Incidence; D008297:Male; D008875:Middle Aged; D033262:Narration; D009323:Natural Language Processing; D018570:Risk Assessment / Q000379:methods; D018875:Vocabulary, Controlled
keywords: Corpus; Machine learning; Medical records; NLP