ArticleIntensive care medicine2018
What's new in ICU in 2050: big data and machine learning.
Article in Intensive care medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 2 of them syntheses that pooled it.
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
24 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Clinical- and surgery-specific risk factors for post-operative sepsis: a systematic review and meta-analysis of over 30 million patients.Surgery today · 2020Pooled it
- Use of machine learning to analyse routinely collected intensive care unit data: a systematic review.Critical care (London, England) · 2019Pooled it
- Random forest-driven mortality prediction in critical IBD care: a dual-database model integrating comorbidity patterns and real-time physiometrics.Frontiers in medicine · 2025Article
- Roadmap for the evolution of monitoring: developing and evaluating waveform-based variability-derived artificial intelligence-powered predictive clinical decision support software tools.Critical care (London, England) · 2024Review
- Discrepancy between perceptions and acceptance of clinical decision support Systems: implementation of artificial intelligence for vancomycin dosing.BMC medical informatics and decision making · 2023Article
- Development and Trends in Artificial Intelligence in Critical Care Medicine: A Bibliometric Analysis of Related Research over the Period of 2010-2021.Journal of personalized medicine · 2022Article
- Development and Validation of Machine Learning Models for Real-Time Mortality Prediction in Critically Ill Patients With Sepsis-Associated Acute Kidney Injury.Frontiers in medicine · 2022Article
- Automatic variable selection in ecological niche modeling: A case study using Cassin's Sparrow (Peucaea cassinii).PloS one · 2022Article
- Risk prediction of clinical adverse outcomes with machine learning in a cohort of critically ill patients with atrial fibrillation.Scientific reports · 2021Article
- Validation of an Automatic Tagging System for Identifying Respiratory and Hemodynamic Deterioration Events in the Intensive Care Unit.Healthcare informatics research · 2021Article
- Sharing ICU Patient Data Responsibly Under the Society of Critical Care Medicine/European Society of Intensive Care Medicine Joint Data Science Collaboration: The Amsterdam University Medical Centers Database (AmsterdamUMCdb) Example.Critical care medicine · 2021Article
- A novel artificial intelligence-assisted triage tool to aid in the diagnosis of suspected COVID-19 pneumonia cases in fever clinics.Annals of translational medicine · 2021Article
- An Automated Scoring of Clinical Asthma Score: Proof of Concept and the Future Possibility.Critical care explorations · 2021Article
- The Visual Dictionary of Antimicrobial Stewardship, Infection Control, and Institutional Surveillance Data.Frontiers in microbiology · 2021Article
- Critical care nursing workforce: Global imperatives, innovations and future-proofing - A call for papers.Intensive & critical care nursing · 2020Article
- Early diagnosis of bloodstream infections in the intensive care unit using machine-learning algorithms.Intensive care medicine · 2020Article
- Artificial intelligence in intensive care: are we there yet?Intensive care medicine · 2019Article
- Machine learning versus physicians' prediction of acute kidney injury in critically ill adults: a prospective evaluation of the AKIpredictor.Critical care (London, England) · 2019Observational
- A deep learning model for real-time mortality prediction in critically ill children.Critical care (London, England) · 2019Observational
- Rationalizing antimicrobial therapy in the ICU: a narrative review.Intensive care medicine · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
Indexed as
Identifiers
29279970What 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.