ArticleIntensive care medicine2021
Artificial intelligence in intensive care medicine.
Article in Intensive care medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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
17 citing papers in PubMed.
- A Review of the Role of Artificial Intelligence in Patients on Extracorporeal Membrane Oxygenation: A Scoping Review Study.Health science reports · 2026Review
- Development and internal validation of an interpretable machine learning model to predict coagulopathy following extracorporeal membrane oxygenation: a retrospective multicenter study.Scandinavian journal of trauma, resuscitation and emergency medicine · 2026Article
- Using machine learning to predict neurologic injury in venovenous extracorporeal membrane oxygenation recipients: An ELSO Registry analysis.JTCVS open · 2024Article
- Artificial Intelligence to Close the Gap between Pharmacokinetic/Pharmacodynamic Targets and Clinical Outcomes in Critically Ill Patients: A Narrative Review on Beta Lactams.Antibiotics (Basel, Switzerland) · 2024Review
- Article
- A Review of Machine Learning Approaches for Brain Positron Emission Tomography Data Analysis.Nuclear medicine and molecular imaging · 2024Review
- Article
- Building a house without foundations? A 24-country qualitative interview study on artificial intelligence in intensive care medicine.BMJ health & care informatics · 2024Article
- Predicting Acute Brain Injury in Venoarterial Extracorporeal Membrane Oxygenation Patients with Tree-Based Machine Learning: Analysis of the Extracorporeal Life Support Organization Registry.Research square · 2024Article
- Role of artificial intelligence in haemodynamic monitoring.Indian journal of anaesthesia · 2024Article
- Utilizing Machine Learning to Predict Neurological Injury in Venovenous Extracorporeal Membrane Oxygenation Patients: An Extracorporeal Life Support Organization Registry Analysis.Research square · 2023Article
- ECMO PAL: using deep neural networks for survival prediction in venoarterial extracorporeal membrane oxygenation.Intensive care medicine · 2023Article
- The physiological underpinnings of life-saving respiratory support.Intensive care medicine · 2022Review
- Prediction algorithm for ICU mortality and length of stay using machine learning.Scientific reports · 2022Article
- Guiding Efficient, Effective, and Patient-Oriented Electrolyte Replacement in Critical Care: An Artificial Intelligence Reinforcement Learning Approach.Journal of personalized medicine · 2022Article
- Ignorance Isn't Bliss: We Must Close the Machine Learning Knowledge Gap in Pediatric Critical Care.Frontiers in pediatrics · 2022Article
- Leaving a mark: pressure injury research in the intensive care unit.Intensive care medicine · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
Indexed as
Identifiers
32767073What 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.