Comparative analysis, applications, and interpretation of electronic health record-based stroke phenotyping methods.

Thangaraj, Phyllis M; Kummer, Benjamin R; Lorberbaum, Tal; Elkind, Mitchell S V; Tatonetti, Nicholas P

Thangaraj, Phyllis M; Kummer, Benjamin R; Lorberbaum, Tal; Elkind, Mitchell S V; Tatonetti, Nicholas P.

Afiliación

Thangaraj PM; Department of Biomedical Informatics, Columbia University, 622 W 168th St., PH-20, New York, NY, 10032, USA.
Kummer BR; Department of Systems Biology, Columbia University, New York, NY, USA.
Lorberbaum T; Department of Neurology, Icahn School of Medicine at Mt. Sinai, New York, NY, USA.
Elkind MSV; Department of Biomedical Informatics, Columbia University, 622 W 168th St., PH-20, New York, NY, 10032, USA.
Tatonetti NP; Department of Systems Biology, Columbia University, New York, NY, USA.

BioData Min ; 13(1): 21, 2020 Dec 07.

Article en En | MEDLINE | ID: mdl-33372632

Palabras clave

Acute ischemic stroke; Electronic health record studies; Machine learning; Phenotyping algorithms

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Guideline / Prognostic_studies / Risk_factors_studies Idioma: En Revista: BioData Min Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido

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