Machine Learning-Based Systems for the Anticipation of Adverse Events After Pediatric Cardiac Surgery

Machine Learning-Based Systems for the Anticipation of Adverse Events After Pediatric Cardiac Surgery

Pediatric congenital heart disease (CHD) patients are at higher risk of postoperative complications and clinical deterioration either due to their underlying pathology or due to the cardiac surgery, contributing significantly to mortality, morbidity, hospital and family costs, and poor quality of li...

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Bibliographic Details
Main Authors: Patricia Garcia-Canadilla, Alba Isabel-Roquero, Esther Aurensanz-Clemente, Arnau Valls-Esteve, Francesca Aina Miguel, Daniel Ormazabal, Floren Llanos, Joan Sanchez-de-Toledo
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-06-01
Series:Frontiers in Pediatrics
Subjects:
artificial intelligence
machine learning
pediatric cardiology
intensive cardiac care
congenital heart disease
early warning score (EWS)
Online Access:https://www.frontiersin.org/articles/10.3389/fped.2022.930913/full

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