AIMC Topic: Ventilator Weaning
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Physiological comparison of noninvasive ventilation and high-flow nasal oxygen on inspiratory efforts and tidal volumes after extubation: a randomized crossover trial.
Critical care (London, England)
May 8, 2025
BACKGROUND: Extubation failure leading to reintubation is associated with high mortality. In patients at high-risk of extubation failure, clinical practice guidelines recommend prophylactic non-invasive ventilation (NIV) over high-flow nasal oxygen (...
An explainable artificial intelligence framework for weaning outcomes prediction using features from electrical impedance tomography.
Computer methods and programs in biomedicine
Apr 25, 2025
BACKGROUND: Prolonged mechanical ventilation (PMV) might cause ventilator-associated pneumonia and diaphragmatic injury, and may lead to worsening clinical weaning outcomes. The present study proposes a comprehensive machine learning (ML) framework f...
Harnessing machine learning for predicting successful weaning from mechanical ventilation: A systematic review.
Australian critical care : official journal of the Confederation of Australian Critical Care Nurses
Mar 9, 2025
BACKGROUND: Machine learning (ML) models represent advanced computational approaches with increasing application in predicting successful weaning from mechanical ventilation (MV). Whilst ML itself has a long history, its application to MV weaning out...
Tailoring ventilation and respiratory management in pediatric critical care: optimizing care with precision medicine.
Current opinion in pediatrics
Feb 12, 2025
PURPOSE OF REVIEW: Critically ill children admitted to the intensive care unit frequently need respiratory care to support the lung function. Mechanical ventilation is a complex field with multiples parameters to set. The development of precision med...
Machine learning-based risk prediction model construction of difficult weaning in ICU patients with mechanical ventilation.
Scientific reports
Sep 6, 2024
In intensive care unit (ICU) patients undergoing mechanical ventilation (MV), the occurrence of difficult weaning contributes to increased ventilator-related complications, prolonged hospitalization duration, and a significant rise in healthcare cost...
Letter to the Editor: "Development of a machine learning model for prediction of the duration of unassisted spontaneous breathing in patients during prolonged weaning from mechanical ventilation".
Journal of critical care
Jun 25, 2024
Authors' response: "Development of a machine learning model for prediction of the duration of unassisted spontaneous breathing in patients during prolonged weaning from mechanical ventilation".
Journal of critical care
Jun 21, 2024
Predicting Extubation Readiness in Preterm Infants Utilizing Machine Learning: A Diagnostic Utility Study.
The Journal of pediatrics
Mar 30, 2024
OBJECTIVE: The objective of this study was to predict extubation readiness in preterm infants using machine learning analysis of bedside pulse oximeter and ventilator data.
Development of a machine learning model for prediction of the duration of unassisted spontaneous breathing in patients during prolonged weaning from mechanical ventilation.
Journal of critical care
Mar 26, 2024
PURPOSE: Treatment of patients undergoing prolonged weaning from mechanical ventilation includes repeated spontaneous breathing trials (SBTs) without respiratory support, whose duration must be balanced critically to prevent over- and underload of re...
Deep learning radiomics on shear wave elastography and b-mode ultrasound videos of diaphragm for weaning outcome prediction.
Medical engineering & physics
Dec 17, 2023
PURPOSE: We proposed an automatic method based on deep learning radiomics (DLR) on shear wave elastography (SWE) and B-mode ultrasound videos of diaphragm for two classification tasks, one for differentiation between the control and patient groups, a...
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