Impact of Different Approaches to Preparing Notes for Analysis With Natural Language Processing on the Performance of Prediction Models in Intensive Care.

Mahendra, Malini; Luo, Yanting; Mills, Hunter; Schenk, Gundolf; Butte, Atul J; Dudley, R Adams

Mahendra, Malini; Luo, Yanting; Mills, Hunter; Schenk, Gundolf; Butte, Atul J; Dudley, R Adams.

Afiliación

Mahendra M; Department of Pediatrics, Division of Pediatric Critical Care, UCSF Benioff Children's Hospital, University of California San Francisco, San Francisco, CA.
Luo Y; Philip R. Lee Institute for Health Policy Studies, University of California San Francisco, San Francisco, CA.
Mills H; Philip R. Lee Institute for Health Policy Studies, University of California San Francisco, San Francisco, CA.
Schenk G; Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA.
Butte AJ; Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA.
Dudley RA; Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA.

Crit Care Explor ; 3(6): e0450, 2021 Jun.

Article en En | MEDLINE | ID: mdl-34136824

Palabras clave

clinical notes; critical care; machine learning; mortality; natural language processing

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Crit Care Explor Año: 2021 Tipo del documento: Article País de afiliación: Canadá Pais de publicación: Estados Unidos

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