Non-Invasive Ventilation Failure in Pediatric ICU: A Machine Learning Driven Prediction

<b>Background/Objectives</b>: Non-invasive ventilation (NIV) has emerged as a possible first-step treatment to avoid invasive intubation in pediatric intensive care units (PICUs) due to its advantages in reducing intubation-associated risks. However, the timely identification of NIV failure is cruci...

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Hlavní autoři:	Maria Vittoria Chiaruttini, Giulia Lorenzoni, Marco Daverio, Luca Marchetto, Francesca Izzo, Giovanna Chidini, Enzo Picconi, Claudio Nettuno, Elisa Zanonato, Raffaella Sagredini, Emanuele Rossetti, Maria Cristina Mondardini, Corrado Cecchetti, Pasquale Vitale, Nicola Alaimo, Denise Colosimo, Francesco Sacco, Giulia Genoni, Daniela Perrotta, Camilla Micalizzi, Silvia Moggia, Giosuè Chisari, Immacolata Rulli, Andrea Wolfler, Angela Amigoni, Dario Gregori
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2024-12-01
Edice:	Diagnostics
Témata:	non-invasive ventilation NIV NIV failure PICU TIPNet machine learning
On-line přístup:	https://www.mdpi.com/2075-4418/14/24/2857
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