Predicting Hemodynamic Failure Development in PICU Using Machine Learning Techniques.

Comoretto, Rosanna I; Azzolina, Danila; Amigoni, Angela; Stoppa, Giorgia; Todino, Federica; Wolfler, Andrea; Gregori, Dario

Comoretto, Rosanna I; Azzolina, Danila; Amigoni, Angela; Stoppa, Giorgia; Todino, Federica; Wolfler, Andrea; Gregori, Dario.

Afiliação

Comoretto RI; Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, 35131 Padova, Italy.
Azzolina D; Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, 35131 Padova, Italy.
Amigoni A; Department of Medical Sciences, University of Ferrara, 44100 Ferrara, Italy.
Stoppa G; Pediatric Intensive Care Unit, Department of Women's and Children's Health, University Hospital of Padua, Via Giustiniani 2, 35128 Padova, Italy.
Todino F; Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, 35131 Padova, Italy.
Wolfler A; Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, 35131 Padova, Italy.
Gregori D; Department of Anaesthesia, Gaslini Hospital, 16147 Genova, Italy.
On Behalf Of The TIPNet Study Group; Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, 35131 Padova, Italy.

Diagnostics (Basel) ; 11(7)2021 Jul 20.

Article em En | MEDLINE | ID: mdl-34359385

Palavras-chave

PICU; hemodynamic failure; imbalance management; machine learning techniques; outcome prediction

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Diagnostics (Basel) Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Itália

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