ArticleScientific reports2021
Machine learning approach to dynamic risk modeling of mortality in COVID-19: a UK Biobank study.
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 12 papers, 1 of them a synthesis that pooled it.
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The trial behind it
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 0 citations in OpenAlex.
- Artificial intelligence-driven prediction of COVID-19-related hospitalization and death: a systematic review.Frontiers in public health · 2023Pooled it
- Identifying direct risk factors in UK Biobank via simultaneous Bayesian-frequentist model-averaged hypothesis testing using Doublethink.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Development of a machine learning-based mortality prediction model for patients with mental disorders and COVID-19.Frontiers in cellular and infection microbiology · 2026Article
- Unlocking the potential of big data and AI in medicine: insights from biobanking.Frontiers in medicine · 2024Article
- Feasibility of using intermittent active monitoring of vital signs by smartphone users to predict SARS-CoV-2 PCR positivity.Scientific reports · 2023Article
- Diagnosis of COVID-19 Using Chest X-ray Images and Disease Symptoms Based on Stacking Ensemble Deep Learning.Diagnostics (Basel, Switzerland) · 2023Article
- Generalizable machine learning approach for COVID-19 mortality risk prediction using on-admission clinical and laboratory features.Scientific reports · 2023Article
- Healthcare data quality assessment for improving the quality of the Korea Biobank Network.PloS one · 2023Article
- A predictive model for hospitalization and survival to COVID-19 in a retrospective population-based study.Scientific reports · 2022Article
- AD-CovNet: An exploratory analysis using a hybrid deep learning model to handle data imbalance, predict fatality, and risk factors in Alzheimer's patients with COVID-19.Computers in biology and medicine · 2022Article
- A Survey on the Role of Artificial Intelligence in Biobanking Studies: A Systematic Review.Diagnostics (Basel, Switzerland) · 2022Review
- Learning and Predicting from Dynamic Models for COVID-19 Patient Monitoring.Statistical science : a review journal of the Institute of Mathematical Statistics · 2022Article
Corrections and comments
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Authors and funding
12 authors at 5 institutions in 3 countries.
Funding
Abstract
The COVID-19 pandemic has created an urgent need for robust, scalable monitoring tools supporting stratification of high-risk patients. This research aims to develop and validate prediction models, using the UK Biobank, to estimate COVID-19 mortality risk in confirmed cases. From the 11,245 participants testing positive for COVID-19, we develop a data-driven random forest classification model with excellent performance (AUC: 0.91), using baseline characteristics, pre-existing conditions, symptoms, and vital signs, such that the score could dynamically assess mortality risk with disease deterioration. We also identify several significant novel predictors of COVID-19 mortality with equivalent or greater predictive value than established high-risk comorbidities, such as detailed anthropometrics and prior acute kidney failure, urinary tract infection, and pneumonias. The model design and feature selection enables utility in outpatient settings. Possible applications include supporting individual-level risk profiling and monitoring disease progression across patients with COVID-19 at-scale, especially in hospital-at-home settings.
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Registered trials
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