Developing a machine-learning model for real-time prediction of successful extubation in mechanically ventilated patients using time-series ventilator-derived …

KY Huang, YL Hsu, HC Chen, MH Horng… - Frontiers in …, 2023 - frontiersin.org
Background Successful weaning from mechanical ventilation is important for patients
admitted to intensive care units. However, models for predicting real-time weaning outcomes …

Machine learning for predicting successful extubation in patients receiving mechanical ventilation

Y Igarashi, K Ogawa, K Nishimura, S Osawa… - Frontiers in …, 2022 - frontiersin.org
Ventilator liberation is one of the most critical decisions in the intensive care unit; however,
prediction of extubation failure is difficult, and the proportion thereof remains high. Machine …

Interpretable recurrent neural network models for dynamic prediction of the extubation failure risk in patients with invasive mechanical ventilation in the intensive care …

Z Zeng, X Tang, Y Liu, Z He, X Gong - Biodata Mining, 2022 - Springer
Background Clinical decision of extubation is a challenge in the treatment of patient with
invasive mechanical ventilation (IMV), since existing extubation protocols are not capable of …

Explainable machine learning approach to predict extubation in critically ill ventilated patients: a retrospective study in central Taiwan

KC Pai, SA Su, MC Chan, CL Wu, WC Chao - BMC anesthesiology, 2022 - Springer
Background Weaning from mechanical ventilation (MV) is an essential issue in critically ill
patients, and we used an explainable machine learning (ML) approach to establish an …

Machine learning for prediction of successful extubation of mechanical ventilated patients in an intensive care unit: a retrospective observational study

T Otaguro, H Tanaka, Y Igarashi, T Tagami… - Journal of Nippon …, 2021 - jstage.jst.go.jp
Background: Ventilator weaning protocols are commonly implemented for patients receiving
mechanical ventilation. However, despite such protocols, the rate of extubation failure …

Development and validation of a machine-learning model for prediction of extubation failure in intensive care units

QY Zhao, H Wang, JC Luo, MH Luo, LP Liu… - Frontiers in …, 2021 - frontiersin.org
Background: Extubation failure (EF) can lead to an increased chance of ventilator-
associated pneumonia, longer hospital stays, and a higher mortality rate. This study aimed …

Development of an interactive ai system for the optimal timing prediction of successful weaning from mechanical ventilation for patients in respiratory care centers

KM Liao, SC Ko, CF Liu, KC Cheng, CM Chen, MI Sung… - Diagnostics, 2022 - mdpi.com
Successful weaning from prolonged mechanical ventilation (MV) is an important issue in
respiratory care centers (RCCs). Delayed or premature extubation increases both the risk of …

Development and Validation of a Deep Learning Classifier Using Chest Radiographs to Predict Extubation Success in Patients Undergoing Invasive Mechanical …

P Tandon, KAN Nguyen, M Edalati, P Parchure, G Raut… - Bioengineering, 2024 - mdpi.com
The decision to extubate patients on invasive mechanical ventilation is critical; however,
clinician performance in identifying patients to liberate from the ventilator is poor. Machine …

Developing and validating a machine learning model to predict successful next-day extubation in the ICU

SW Fenske, A Peltekian, M Kang, NS Markov, M Zhu… - medRxiv, 2024 - medrxiv.org
Background: Criteria to identify patients who are ready to be liberated from mechanical
ventilation are imprecise, often resulting in prolonged mechanical ventilation or reintubation …

Prediction of weaning from mechanical ventilation using convolutional neural networks

Y Jia, C Kaul, T Lawton, R Murray-Smith… - Artificial intelligence in …, 2021 - Elsevier
Weaning from mechanical ventilation covers the process of liberating the patient from
mechanical support and removing the associated endotracheal tube. The management of …