Machine-learning model predicting postoperative delirium in older patients using intraoperative frontal electroencephalographic signatures.

Röhr, Vera; Blankertz, Benjamin; Radtke, Finn M; Spies, Claudia; Koch, Susanne

Röhr, Vera; Blankertz, Benjamin; Radtke, Finn M; Spies, Claudia; Koch, Susanne.

Afiliación

Röhr V; Neurotechnology Group, Technische Universität Berlin, Berlin, Germany.
Blankertz B; Neurotechnology Group, Technische Universität Berlin, Berlin, Germany.
Radtke FM; Department of Anaesthesia, Hospital of Nykobing, University of Southern Denmark, Odense, Denmark.
Spies C; Department of Anaesthesiology and Operative Intensive Care Medicine, Charité-Universitätsmedizin Berlin, Berlin, Germany.
Koch S; Department of Anaesthesiology and Operative Intensive Care Medicine, Charité-Universitätsmedizin Berlin, Berlin, Germany.

Front Aging Neurosci ; 14: 911088, 2022.

Article en En | MEDLINE | ID: mdl-36313029

Palabras clave

aging; artificial intelligence; electroencephalography; machine learning; postoperative delirium; prediction model; surgery

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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: Front Aging Neurosci Año: 2022 Tipo del documento: Article País de afiliación: Alemania

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