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Classification of Contextual Use of Left Ventricular Ejection Fraction Assessments.
Kim, Youngjun; Garvin, Jennifer; Goldstein, Mary K; Meystre, Stéphane M.
Afiliación
  • Kim Y; School of Computing, University of Utah, Salt Lake City, USA.
  • Garvin J; Department of Biomedical Informatics, University of Utah, Salt Lake City, USA.
  • Goldstein MK; VA Palo Alto Health Care System, Palo Alto, CA, and Stanford University, Stanford, CA, USA.
  • Meystre SM; Department of Biomedical Informatics, University of Utah, Salt Lake City, USA.
Stud Health Technol Inform ; 216: 599-603, 2015.
Article en En | MEDLINE | ID: mdl-26262121
Knowledge of the left ventricular ejection fraction is critical for the optimal care of patients with heart failure. When a document contains multiple ejection fraction assessments, accurate classification of their contextual use is necessary to filter out historical findings or recommendations and prioritize the assessments for selection of document level ejection fraction information. We present a natural language processing system that classifies the contextual use of both quantitative and qualitative left ventricular ejection fraction assessments in clinical narrative documents. We created support vector machine classifiers with a variety of features extracted from the target assessment, associated concepts, and document section information. The experimental results showed that our classifiers achieved good performance, reaching 95.6% F1-measure for quantitative assessments and 94.2% F1-measure for qualitative assessments in a five-fold cross-validation evaluation.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Volumen Sistólico / Procesamiento de Lenguaje Natural / Diagnóstico por Computador / Sistemas de Apoyo a Decisiones Clínicas / Registros Electrónicos de Salud / Insuficiencia Cardíaca Tipo de estudio: Diagnostic_studies / Guideline / Prognostic_studies / Qualitative_research Límite: Humans Idioma: En Revista: Stud Health Technol Inform Asunto de la revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Año: 2015 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Países Bajos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Volumen Sistólico / Procesamiento de Lenguaje Natural / Diagnóstico por Computador / Sistemas de Apoyo a Decisiones Clínicas / Registros Electrónicos de Salud / Insuficiencia Cardíaca Tipo de estudio: Diagnostic_studies / Guideline / Prognostic_studies / Qualitative_research Límite: Humans Idioma: En Revista: Stud Health Technol Inform Asunto de la revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Año: 2015 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Países Bajos