ArticleMedicina (Kaunas, Lithuania)2022
The Feasibility of a Machine Learning Approach in Predicting Successful Ventilator Mode Shifting for Adult Patients in the Medical Intensive Care Unit.
Article in Medicina (Kaunas, Lithuania), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 19 citations in OpenAlex.
- Artificial intelligence in mechanical ventilation: a narrative review of clinical applications and research gaps.Journal of thoracic disease · 2026Review
- Feature selection methodology based on explainable AI: application in predicting extubation success in the intensive care unit.Scientific reports · 2026Article
- Developing and validating machine learning models to predict next-day extubation.Scientific reports · 2025Article
- Advances in Machine Learning for Mechanically Ventilated Patients.International journal of general medicine · 2025Review
- Enhancing machine learning performance in cardiac surgery ICU: Hyperparameter optimization with metaheuristic algorithm.PloS one · 2025Article
- Dual-phase machine learning framework for paediatric ventilator liberation: forecasting extubation readiness and nowcasting extubation outcomes.BMJ digital health & AI · 2025Article
- Artificial Intelligence in the Management of Patients with Respiratory Failure Requiring Mechanical Ventilation: A Scoping Review.Journal of clinical medicine · 2024Article
- Using Artificial Intelligence to Predict Mechanical Ventilation Weaning Success in Patients with Respiratory Failure, Including Those with Acute Respiratory Distress Syndrome.Journal of clinical medicine · 2024Review
- Predicting Successful Weaning from Mechanical Ventilation by Reduction in Positive End-expiratory Pressure Level Using Machine Learning.PLOS digital health · 2024Article
- Explainable machine learning approach to predict extubation in critically ill ventilated patients: a retrospective study in central Taiwan.BMC anesthesiology · 2022Article
- An artificial intelligence system to predict the optimal timing for mechanical ventilation weaning for intensive care unit patients: A two-stage prediction approach.Frontiers in medicine · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.