title: Abbreviation and acronym disambiguation in clinical discourse.
abstract: Use of abbreviations and acronyms is pervasive in clinical reports despite many efforts to limit the use of ambiguous and unsanctioned abbreviations and acronyms. Due to the fact that many abbreviations and acronyms are ambiguous with respect to their sense, complete and accurate text analysis is impossible without identification of the sense that was intended for a given abbreviation or acronym. We present the results of an experiment where we used the contexts harvested from the Internet through Google API to collect contextual data for a set of 8 acronyms found in clinical notes at the Mayo Clinic. We then used the contexts to disambiguate the sense of abbreviations in a manually annotated corpus.
authors.affiliation: Division of Biomedical Informatics, Mayo College of Medicine, Rochester, MN, USA.
authors.forename: Sergeui
authors.initials: S
authors.lastname: Pakhomov
authors.forename: Ted
authors.initials: T
authors.lastname: Pedersen
authors.forename: Christopher G
authors.initials: CG
authors.lastname: Chute
mesh_terms: D000004:Abbreviations as Topic; D000465:Algorithms; D001185:Artificial Intelligence; D020407:Internet; D008499:Medical Records; D009323:Natural Language Processing