Standard Vocabularies to Improve Machine Learning Model Transferability With Electronic Health Record Data: Retrospective Cohort Study Using Health Care-Associated Infection.

Kiser, Amber C; Eilbeck, Karen; Ferraro, Jeffrey P; Skarda, David E; Samore, Matthew H; Bucher, Brian

Kiser, Amber C; Eilbeck, Karen; Ferraro, Jeffrey P; Skarda, David E; Samore, Matthew H; Bucher, Brian.

Afiliação

Kiser AC; Department of Biomedical Informatics, School of Medicine, University of Utah, Salt Lake City, UT, United States.
Eilbeck K; Department of Biomedical Informatics, School of Medicine, University of Utah, Salt Lake City, UT, United States.
Ferraro JP; Department of Medicine, School of Medicine, University of Utah, Salt Lake City, UT, United States.
Skarda DE; Center for Value-Based Surgery, Intermountain Healthcare, Salt Lake City, UT, United States.
Samore MH; Department of Surgery, School of Medicine, University of Utah, Salt Lake City, UT, United States.
Bucher B; Department of Medicine, School of Medicine, University of Utah, Salt Lake City, UT, United States.

JMIR Med Inform ; 10(8): e39057, 2022 Aug 30.

Article em En | MEDLINE | ID: mdl-36040784

Palavras-chave

data heterogeneity; electronic health records; machine learning; model transferability; standard vocabularies

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: JMIR Med Inform Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

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