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Using natural language processing to identify opioid use disorder in electronic health record data.
Singleton, Jade; Li, Chengxi; Akpunonu, Peter D; Abner, Erin L; Kucharska-Newton, Anna M.
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  • Singleton J; Department of Epidemiology, College of Public Health, University of Kentucky, Lexington, KY 40536, United States; University of Kentucky Healthcare IT Department, Business Intelligence, Lexington, KY 40517, United States. Electronic address: jade.singleton@seattlechildrens.org.
  • Li C; Department of Computer Science, College of Engineering, University of Kentucky, Lexington, KY 40526, United States.
  • Akpunonu PD; Emergency Medicine & Medical Toxicology, University of Kentucky Hospital, Lexington, KY 40536, United States.
  • Abner EL; Department of Epidemiology, College of Public Health, University of Kentucky, Lexington, KY 40536, United States.
  • Kucharska-Newton AM; Department of Epidemiology, College of Public Health, University of Kentucky, Lexington, KY 40536, United States; Department of Epidemiology, The Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, United States.
Int J Med Inform ; 170: 104963, 2023 02.
Article en En | MEDLINE | ID: mdl-36521420
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Procesamiento de Lenguaje Natural / Trastornos Relacionados con Opioides Tipo de estudio: Diagnostic_studies / Guideline / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Int J Med Inform Asunto de la revista: INFORMATICA MEDICA Año: 2023 Tipo del documento: Article
Texto completo
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Procesamiento de Lenguaje Natural / Trastornos Relacionados con Opioides Tipo de estudio: Diagnostic_studies / Guideline / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Int J Med Inform Asunto de la revista: INFORMATICA MEDICA Año: 2023 Tipo del documento: Article