Predicting sepsis using deep learning across international sites: a retrospective development and validation study.

Moor, Michael; Bennett, Nicolas; Plecko, Drago; Horn, Max; Rieck, Bastian; Meinshausen, Nicolai; Bühlmann, Peter; Borgwardt, Karsten

Moor, Michael; Bennett, Nicolas; Plecko, Drago; Horn, Max; Rieck, Bastian; Meinshausen, Nicolai; Bühlmann, Peter; Borgwardt, Karsten.

Afiliação

Moor M; Department of Biosystems Science and Engineering, ETH Zurich, Basel 4058, Switzerland.
Bennett N; SIB Swiss Institute of Bioinformatics, Switzerland.
Plecko D; Department of Computer Science, Stanford University, Stanford, CA, USA.
Horn M; Seminar for Statistics, Department of Mathematics, ETH Zurich, Switzerland.
Rieck B; Seminar for Statistics, Department of Mathematics, ETH Zurich, Switzerland.
Meinshausen N; Department of Biosystems Science and Engineering, ETH Zurich, Basel 4058, Switzerland.
Bühlmann P; SIB Swiss Institute of Bioinformatics, Switzerland.
Borgwardt K; Department of Biosystems Science and Engineering, ETH Zurich, Basel 4058, Switzerland.

EClinicalMedicine ; 62: 102124, 2023 Aug.

Article em En | MEDLINE | ID: mdl-37588623

Palavras-chave

Deep learning; Early prediction; Early warning; ICU; Intensive care; Machine learning; Sepsis

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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

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