title: Representing clinical questions by semantic type for better classification.
abstract: It is recognized that physicians need information that answers their questions at the point of care. Taxonomic classification of clinical domain questions is a preliminary step in developing real-time answer retrieval systems. We show that using the UMLS semantic types and machine learning algorithms improves classification performance of clinical questions for the generic taxonomic categories.
authors.affiliation: Department of Computer Science, University of Missouri, Columbia, MO 65211, USA.
authors.forename: Tetsuya
authors.initials: T
authors.lastname: Kobayashi
authors.forename: Chi-Ren
authors.initials: CR
authors.lastname: Shyu
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D002965:Classification; D016247:Information Storage and Retrieval; D009323:Natural Language Processing; D012660:Semantics; D017432:Unified Medical Language System; D018875:Vocabulary, Controlled