Using artificial intelligence to predict mechanical ventilation weaning success in patients with respiratory failure, including those with acute respiratory distress …

T Stivi, D Padawer, N Dirini, A Nachshon… - Journal of Clinical …, 2024 - mdpi.com
The management of mechanical ventilation (MV) remains a challenge in intensive care units
(ICUs). The digitalization of healthcare and the implementation of artificial intelligence (AI) …

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 …

The combination of radiomics features and VASARI standard to predict glioma grade

W You, Y Mao, X Jiao, D Wang, J Liu, P Lei… - Frontiers in …, 2023 - frontiersin.org
Background and Purpose Radiomics features and The Visually AcceSAble Rembrandt
Images (VASARI) standard appear to be quantitative and qualitative evaluations utilized to …

Lung ultrasound score as a predictor of failure to wean COVID-19 elderly patients off mechanical ventilation: a prospective observational study

Y Wang, Y Yi, F Zhang, YY Yao, YX Chen… - … Interventions in Aging, 2024 - Taylor & Francis
Background The lung ultrasound score was developed for rapidly assessing the extent of
lung ventilation, and it can predict failure to wean various types of patients off mechanical …

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 …

Risk factor analysis and multiple predictive machine learning models for mortality in COVID-19: a multicenter and multi-ethnic cohort study

Y Shi, Y Qin, Z Zheng, P Wang, J Liu - The Journal of Emergency Medicine, 2023 - Elsevier
Background The COVID-19 pandemic presents a significant challenge to the global health
care system. Implementing timely, accurate, and cost-effective screening approaches is …

Humidified noninvasive ventilation versus high-flow therapy to prevent reintubation in patients with obesity: a randomized clinical trial

G Hernández, J Dianti, I Paredes, F Moran… - American Journal of …, 2025 - atsjournals.org
Rationale: The optimal strategy to prevent reintubation in patients with obesity remains
uncertain. Objectives: We aimed to determine whether noninvasive ventilation (NIV) with …

[HTML][HTML] The intervention of artificial intelligence to improve the weaning outcomes of patients with mechanical ventilation: Practical applications in the medical …

YH Lin, TC Chang, CF Liu, CC Lai, CM Chen, W Chou - Medicine, 2024 - journals.lww.com
Patients admitted to intensive care units (ICU) and receiving mechanical ventilation (MV)
may experience ventilator-associated adverse events and have prolonged ICU length of …

Physical frailty identification using machine learning to explore the 5-item FRAIL scale, Cardiovascular Health Study index, and Study of Osteoporotic Fractures index

CC Yang, PH Chen, CH Yang, CY Dai… - Frontiers in Public …, 2024 - frontiersin.org
Background Physical frailty is an important issue in aging societies. Three models of
physical frailty assessment, the 5-Item fatigue, resistance, ambulation, illness and loss of …

Biomarkers as predictors of mortality in critically ill obese patients with COVID-19 at high altitude

JL Vélez-Páez, SX Aguayo-Moscoso… - BMC Pulmonary …, 2023 - Springer
Background Obesity is a common chronic comorbidity of patients with COVID-19, that has
been associated with disease severity and mortality. COVID-19 at high altitude seems to be …