title: Annotating temporal information in clinical narratives.
abstract: Temporal information in clinical narratives plays an important role in patients' diagnosis, treatment and prognosis. In order to represent narrative information accurately, medical natural language processing (MLP) systems need to correctly identify and interpret temporal information. To promote research in this area, the Informatics for Integrating Biology and the Bedside (i2b2) project developed a temporally annotated corpus of clinical narratives. This corpus contains 310 de-identified discharge summaries, with annotations of clinical events, temporal expressions and temporal relations. This paper describes the process followed for the development of this corpus and discusses annotation guideline development, annotation methodology, and corpus quality.
authors.affiliation: Department of Informatics, University at Albany, SUNY, 1400 Washington Ave., Draper 114B, Albany, NY 12222, United States. Electronic address: wsun2@albany.edu.
authors.forename: Weiyi
authors.initials: W
authors.lastname: Sun
authors.affiliation: Department of Computer Science, University of Massachusetts, 198 Riverside St., Olsen Hall, Lowell, MA 01854, United States.
authors.forename: Anna
authors.initials: A
authors.lastname: Rumshisky
authors.affiliation: Department of Information Studies, University at Albany, SUNY, 1400 Washington Ave., Draper 114A, Albany, NY 12222, United States.
authors.forename: Ozlem
authors.initials: O
authors.lastname: Uzuner
mesh_terms: D004282:Documentation / Q000379:methods*; D057286:Electronic Health Records; D006801:Humans; D008490:Medical Informatics / Q000379:methods*; D033262:Narration; D009323:Natural Language Processing
keywords: Annotation; Corpus Building; Medical Informatics; Natural Language Processing; Temporal Reasoning