AIMC Topic: Airway Extubation

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Expert-augmented machine learning for predicting extubation readiness in the pediatric intensive care unit.

BMC medical informatics and decision making Jul 1, 2025
BACKGROUND: Determining extubation readiness in pediatric intensive care units (PICU) is challenging. We used expert-augmented machine learning (EAML), a method that combines machine learning with human expert knowledge, to predict successful extubat...
Humans Machine Learning Electronic Health Records Child, Preschool Child Intensive Care Units, Pediatric Airway Extubation Female Male Infant
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Using ML techniques to predict extubation outcomes for patients with central nervous system injuries in the Yun-Gui Plateau.

Scientific reports May 22, 2025
No predictive models have been reported for tracheostomy extubation success in plateau region rehabilitation departments. Hence, the primary objective of this retrospective study was to evaluate the predictive capabilities of different models for ext...
Tracheostomy China Treatment Outcome Airway Extubation Male Humans Aged Retrospective Studies Middle Aged Adult Female
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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 (...
Tidal Volume Cross-Over Studies Airway Extubation Aged Ventilator Weaning Humans Oxygen Inhalation Therapy Aged, 80 and over Prospective Studies Noninvasive Ventilation Male Female
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Development and validation of machine learning models for predicting extubation failure in patients undergoing cardiac surgery: a retrospective study.

Scientific reports Mar 12, 2025
Patients with multiple comorbidities and those undergoing complex cardiac surgery may experience extubation failure and reintubation. The aim of this study was to establish an extubation prediction model using explainable machine learning and identif...
Humans Machine Learning Algorithms Retrospective Studies Middle Aged Cardiac Surgical Procedures Airway Extubation Female Aged Male
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Using machine-learning models to predict extubation failure in neonates with bronchopulmonary dysplasia.

BMC pulmonary medicine Jul 1, 2024
AIM: To develop a decision-support tool for predicting extubation failure (EF) in neonates with bronchopulmonary dysplasia (BPD) using a set of machine-learning algorithms.
Respiration, Artificial ROC Curve Logistic Models Infant, Newborn Male Bronchopulmonary Dysplasia Nomograms Airway Extubation Treatment Failure Humans Retrospective Studies Female Machine Learning Decision Support Techniques
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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.
Oximetry Ventilator Weaning Infant, Premature Gestational Age Airway Extubation Humans Machine Learning ROC Curve Infant, Newborn Hypoxia Male Oxygen Saturation Prospective Studies Female
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Artificial intelligence in the NICU to predict extubation success in prematurely born infants.

Journal of perinatal medicine Dec 8, 2023
OBJECTIVES: Mechanical ventilation in prematurely born infants, particularly if prolonged, can cause long term complications including bronchopulmonary dysplasia. Timely extubation then is essential, yet predicting its success remains challenging. Ar...
Humans Intensive Care Units, Neonatal Infant Respiration, Artificial Airway Extubation Artificial Intelligence Forecasting Infant, Newborn
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Building a better machine learning model of extubation for neurocritical care patients. Author's reply.

Intensive care medicine Dec 7, 2022
Humans Airway Extubation Machine Learning Critical Care
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Early prediction of noninvasive ventilation failure after extubation: development and validation of a machine-learning model.

BMC pulmonary medicine Aug 8, 2022
BACKGROUND: Noninvasive ventilation (NIV) has been widely used in critically ill patients after extubation. However, NIV failure is associated with poor outcomes. This study aimed to determine early predictors of NIV failure and to construct an accur...
Airway Extubation Noninvasive Ventilation Respiration, Artificial Oxygen Respiratory Insufficiency Machine Learning Intensive Care Units Reproducibility of Results Humans
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Machine Learning in Laryngoscopy Analysis: A Proof of Concept Observational Study for the Identification of Post-Extubation Ulcerations and Granulomas.

The Annals of otology, rhinology, and laryngology Aug 14, 2020
OBJECTIVE: Computer-aided analysis of laryngoscopy images has potential to add objectivity to subjective evaluations. Automated classification of biomedical images is extremely challenging due to the precision required and the limited amount of annot...
Respiration, Artificial Intubation, Intratracheal Neural Networks, Computer Image Processing, Computer-Assisted Larynx Airway Extubation Machine Learning Humans Proof of Concept Study Granuloma, Laryngeal Ulcer Intensive Care Units Laryngoscopy
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