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Automatic generation of repeated patient information for tailoring clinical notes.
Meng, Frank; Taira, Ricky K; Bui, Alex A T; Kangarloo, Hooshang; Churchill, Bernard M.
Afiliación
  • Meng F; UCLA Medical Informatics Group, University of California-Los Angeles, 924 Westwood Boulevard Suite 420, Los Angeles, CA 90024, USA. fmeng@itmedicine.net
Stud Health Technol Inform ; 107(Pt 1): 653-7, 2004.
Article en En | MEDLINE | ID: mdl-15360894
ABSTRACT
Dictating clear, readable, and accurate clinical notes can be a time-consuming task for physicians. Clinical notes often contain information concerning the patient's medical history and current medical condition which is propagated from one clinical note to all follow-up clinical notes for the same patient. In this paper, we present a system which, given a clinical note, automatically determines what information should be repeated, and then generates this information for the physician for a new clinical note. We use semantic patterns for capturing the rhetorical category of sentences, which we show to be useful for determining whether the sentence should be repeated. Our system is shown to perform better than a baseline metric based on precision/recall results. Such a system would allow clinical notes to be more complete, timely, and accurate.
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Bases de datos: MEDLINE Asunto principal: Procesamiento de Lenguaje Natural / Sistemas de Registros Médicos Computarizados Tipo de estudio: Evaluation_studies Límite: Humans Idioma: En Revista: Stud Health Technol Inform Asunto de la revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Año: 2004 Tipo del documento: Article País de afiliación: Estados Unidos
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Bases de datos: MEDLINE Asunto principal: Procesamiento de Lenguaje Natural / Sistemas de Registros Médicos Computarizados Tipo de estudio: Evaluation_studies Límite: Humans Idioma: En Revista: Stud Health Technol Inform Asunto de la revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Año: 2004 Tipo del documento: Article País de afiliación: Estados Unidos