title: Using NLP to extract concepts from chief complaints.
abstract: The NLM's MMTx natural language processing (NLP) engine was used to extract concepts from chief complaints entered into an ambulatory electronic medical record (EMR). Of the over 600,000 strings submitted to the process, approximately 25% were assigned at least one concept, with a rate of 2% for incorrect assignments.
authors.affiliation: GE Healthcare Technologies, Waukesha Wisconsin, and Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, USA.
authors.forename: Michael I
authors.initials: MI
authors.lastname: Lieberman
authors.forename: Thomas N
authors.initials: TN
authors.lastname: Ricciardi
mesh_terms: D000043:Abstracting and Indexing; D000555:Ambulatory Care Information Systems; D006801:Humans; D016247:Information Storage and Retrieval; D016347:Medical Records Systems, Computerized; D009323:Natural Language Processing; D017432:Unified Medical Language System