ArticleScientific reports2021
Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 2 of them syntheses that pooled it.
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Who cites it
47 citing papers in PubMed, 2 syntheses or guidelines pooled it, 85 citations in OpenAlex.
- Prognostic models in COVID-19 infection that predict severity: a systematic review.European journal of epidemiology · 2023Pooled it
- Artificial intelligence-driven prediction of COVID-19-related hospitalization and death: a systematic review.Frontiers in public health · 2023Pooled it
- Machine learning application for the prediction of SARS-CoV-2 infection using blood tests and chest radiograph.Scientific reports · 2021Trial
- Development and External Validation of a Prognostic Prediction Model for Hospitalization in SARS-CoV-2-Infected Ambulatory Patients.Open forum infectious diseases · 2026Article
- Identifying 20 homogeneous clusters of acute patients discharged with nonspecific diagnoses through k-prototypes mixed data clustering.BMC emergency medicine · 2026Observational
- Machine learning-based prediction of intensive care unit admission in COVID-19 patients presenting with mild respiratory failure.Frontiers in medicine · 2026Article
- Calculating the Risk of Admission to Intensive Care Units in COVID-19 Patients Using Machine Learning.Journal of clinical medicine · 2025Article
- Prediction models based on machine learning algorithms for COVID-19 severity risk.BMC public health · 2025Article
- Classification of the ICU Admission for COVID-19 Patients with Transfer Learning Models Using Chest X-Ray Images.Diagnostics (Basel, Switzerland) · 2025Article
- Predicting coronavirus disease 2019 severity using explainable artificial intelligence techniques.Scientific reports · 2025Article
- Predicting Severe Respiratory Failure in Patients with COVID-19: A Machine Learning Approach.Journal of clinical medicine · 2024Article
- Unbiased plasma profiling using pre-selected RNA aptamer pools predicts mortality in COVID-19 and identifies protein risk factors.Molecular therapy. Nucleic acids · 2024Article
- Modeling mortality prediction in older adults with dementia receiving COVID-19 vaccination.BMC geriatrics · 2024Article
- Artificial intelligence in triage of COVID-19 patients.Frontiers in artificial intelligence · 2024Article
- Deep learning in public health: Comparative predictive models for COVID-19 case forecasting.PloS one · 2024Article
- COVID-19-associated cerebral microbleeds in the general population.Brain communications · 2024Article
- Predictors of Intensive Care Unit Admissions in Patients Presenting with Coronavirus Disease 2019.Avicenna journal of medicine · 2024Article
- Unlocking the potential of big data and AI in medicine: insights from biobanking.Frontiers in medicine · 2024Article
- Combining blood glucose and SpOScientific reports · 2023Article
- Multimodal graph attention network for COVID-19 outcome prediction.Scientific reports · 2023Article
Corrections and comments
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Authors and funding
35 authors at 8 institutions in 2 countries.
Funding
Abstract
Patients with severe COVID-19 have overwhelmed healthcare systems worldwide. We hypothesized that machine learning (ML) models could be used to predict risks at different stages of management and thereby provide insights into drivers and prognostic markers of disease progression and death. From a cohort of approx. 2.6 million citizens in Denmark, SARS-CoV-2 PCR tests were performed on subjects suspected for COVID-19 disease; 3944 cases had at least one positive test and were subjected to further analysis. SARS-CoV-2 positive cases from the United Kingdom Biobank was used for external validation. The ML models predicted the risk of death (Receiver Operation Characteristics-Area Under the Curve, ROC-AUC) of 0.906 at diagnosis, 0.818, at hospital admission and 0.721 at Intensive Care Unit (ICU) admission. Similar metrics were achieved for predicted risks of hospital and ICU admission and use of mechanical ventilation. Common risk factors, included age, body mass index and hypertension, although the top risk features shifted towards markers of shock and organ dysfunction in ICU patients. The external validation indicated fair predictive performance for mortality prediction, but suboptimal performance for predicting ICU admission. ML may be used to identify drivers of progression to more severe disease and for prognostication patients in patients with COVID-19. We provide access to an online risk calculator based on these findings.
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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.