ReviewJournal of clinical medicine2024
Using Artificial Intelligence to Predict Mechanical Ventilation Weaning Success in Patients with Respiratory Failure, Including Those with Acute Respiratory Distress Syndrome.
Review in Journal of clinical medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
27 citing papers in PubMed.
- Physiology-guided mechanical ventilation: Monitoring, proportional assist, and bounded automation.World journal of critical care medicine · 2026Review
- Effects of Phrenic Nerve Stimulation in Mechanically Ventilated Patients: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.Journal of clinical medicine · 2026Review
- Development of a deep-learning model for classification of intensivists' extubation decisions using ventilator graphic monitor images: a prospective observational study.Journal of intensive care · 2026Article
- Artificial intelligence in ARDS: From automated support to personalized ventilation.Journal of intensive medicine · 2026Article
- Beyond One-Size-Fits-All: Precision Mechanical Ventilation in ARDS.Journal of clinical medicine · 2026Review
- Postoperative complications of coronary artery bypass grafting: a narrative review on pathophysiology, management strategies, and the emerging role of artificial intelligence.Cardiovascular diagnosis and therapy · 2026Review
- Machine learning-driven prediction model for successful weaning of patients from mechanical ventilation in ICU.Intensive care medicine experimental · 2026Article
- Circulating and Respiratory Biomarkers in Sepsis-Induced ARDS: Diagnostic and Prognostic Insights - A Narrative Review.Journal of inflammation research · 2026Review
- Methodological and Clinical Gaps in Biomarker-Guided Weaning for Sepsis-Induced ARDS [Letter].Journal of inflammation research · 2026Article
- Bedside ventilatory settings guided by respiratory mechanics in acute respiratory distress syndrome.Annals of intensive care · 2025Review
- Predicting weaning failure from invasive mechanical ventilation: The promise and pitfalls of clinical prediction scores.World journal of critical care medicine · 2025Review
- AI Model Based on Diaphragm Ultrasound to Improve the Predictive Performance of Invasive Mechanical Ventilation Weaning: Prospective Cohort Study.JMIR formative research · 2025Article
- Optimizing Vital Signs in Patients With Traumatic Brain Injury: Reinforcement Learning Algorithm Development and Validation.Journal of medical Internet research · 2025Article
- Role of artificial intelligence in enhancing mechanical ventilation - A peek into the future.Indian journal of anaesthesia · 2025Article
- Factors influencing weaning success from mechanical ventilation in Emergency department patients with acute respiratory failure.American journal of translational research · 2025Article
- Lung ultrasound score as a tool to assess pulmonary ventilation and disease severity in patients with acute respiratory distress syndrome.American journal of translational research · 2025Article
- Machine learning to predict extubation success using the spontaneous breathing trial, objective cough measurement, and diaphragmatic contraction velocity: Secondary analysis of the COBRE-US trial.Journal of critical care medicine (Universitatea de Medicina si Farmacie din Targu-Mures) · 2025Article
- Transforming critical care: the digital revolution's impact on intensive care units.Frontiers in digital health · 2025Review
- Artificial Intelligence in the Management of Patients with Respiratory Failure Requiring Mechanical Ventilation: A Scoping Review.Journal of clinical medicine · 2024Article
- Challenges in Transitioning from Controlled to Assisted Ventilation in Acute Respiratory Distress Syndrome (ARDS) Management.Journal of clinical medicine · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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) and machine learning (ML) has significantly influenced medical decision-making capabilities, potentially enhancing patient outcomes. Acute respiratory distress syndrome, an overwhelming inflammatory lung disease, is common in ICUs. Most patients require MV. Prolonged MV is associated with an increased length of stay, morbidity, and mortality. Shortening the MV duration has both clinical and economic benefits and emphasizes the need for better MV weaning management. AI and ML models can assist the physician in weaning patients from MV by providing predictive tools based on big data. Many ML models have been developed in recent years, dealing with this unmet need. Such models provide an important prediction regarding the success of the individual patient's MV weaning. Some AI models have shown a notable impact on clinical outcomes. However, there are challenges in integrating AI models into clinical practice due to the unfamiliar nature of AI for many physicians and the complexity of some AI models. Our review explores the evolution of weaning methods up to and including AI and ML as weaning aids.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.