QR Kodea

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...

Deskribapen osoa

Gorde:
Egile Nagusiak: 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
Formatua: Artigo
Hizkuntza:Inglês
Argitaratua: MDPI AG 2024-12-01
Saila:Diagnostics
Gaiak:
non-invasive ventilation
NIV
NIV failure
PICU
TIPNet
machine learning
Sarrera elektronikoa:https://www.mdpi.com/2075-4418/14/24/2857
Etiketak: Etiketa erantsi
Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!

Antzeko izenburuak