Continuous Data-Driven Monitoring in Critical Congenital Heart Disease: Clinical Deterioration Model Development.

Zoodsma, Ruben S; Bosch, Rian; Alderliesten, Thomas; Bollen, Casper W; Kappen, Teus H; Koomen, Erik; Siebes, Arno; Nijman, Joppe

Zoodsma, Ruben S; Bosch, Rian; Alderliesten, Thomas; Bollen, Casper W; Kappen, Teus H; Koomen, Erik; Siebes, Arno; Nijman, Joppe.

Afiliação

Zoodsma RS; Department of Paediatric Intensive Care, University Medical Center Utrecht, Utrecht, Netherlands.
Bosch R; Department of Paediatric Intensive Care, University Medical Center Utrecht, Utrecht, Netherlands.
Alderliesten T; Department of Paediatric Intensive Care, University Medical Center Utrecht, Utrecht, Netherlands.
Bollen CW; Department of Paediatric Intensive Care, University Medical Center Utrecht, Utrecht, Netherlands.
Kappen TH; Department of Anaesthesiology, University Medical Center Utrecht, Utrecht, Netherlands.
Koomen E; Department of Paediatric Intensive Care, University Medical Center Utrecht, Utrecht, Netherlands.
Siebes A; Department of Information and Computing Sciences, Utrecht University, Utrecht, Netherlands.
Nijman J; Department of Paediatric Intensive Care, University Medical Center Utrecht, Utrecht, Netherlands.

JMIR Cardio ; 7: e45190, 2023 May 16.

Article em En | MEDLINE | ID: mdl-37191988

Palavras-chave

aberration detection; artificial intelligence; cardiac monitoring; classification model; clinical deterioration; congenital heart disease; machine learning; paediatric intensive care; pediatric intensive care; peri-operative; perioperative; surgery

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Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: JMIR Cardio Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Holanda

Texto completo

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PubMed Links

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Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: JMIR Cardio Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Holanda