ArticleCritical care (London, England)2020
How machine learning could be used in clinical practice during an epidemic.
Article in Critical care (London, England), 2020. 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.
- Machine learning-enhanced modeling approach for optimally predicting household level food insecurity in Ethiopia during COVID-19.Scientific reports · 2026Article
- Comparative Analysis of 3 Machine Learning Methods for Identifying Minimal Predictors of Patellofemoral Instability Risk Factors.Orthopaedic journal of sports medicine · 2025Article
- Identification of noval diagnostic biomarker for HFpEF based on proteomics and machine learning.Proteome science · 2025Article
- Risk assessment and prediction of nosocomial infections based on surveillance data using machine learning methods.BMC public health · 2024Article
- Machine learning-based predictive models for the occurrence of behavioral and psychological symptoms of dementia: model development and validation.Scientific reports · 2023Article
- Comparison of machine learning methods with logistic regression analysis in creating predictive models for risk of critical in-hospital events in COVID-19 patients on hospital admission.BMC medical informatics and decision making · 2022Article
- Upcoming and urgent challenges in critical care research based on COVID-19 pandemic experience.Anaesthesia, critical care & pain medicine · 2022Review
- Development and validation of a deep-learning-based pediatric early warning system: A single-center study.Biomedical journal · 2022Observational
- Risk assessment in COVID-19 patients: A multiclass classification approach.Informatics in medicine unlocked · 2022Article
- Economic impact of a machine learning-based strategy for preparation of blood products in brain tumor surgery.PloS one · 2022Article
- Visualisation of epidemiological map using an Internet of Things infectious disease surveillance platform.Critical care (London, England) · 2020Article
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.
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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.