ArticleScientific reports2022
A predictive model for hospitalization and survival to COVID-19 in a retrospective population-based study.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 21 citations in OpenAlex.
- Combining label-free Raman spectroscopy and machine learning to identify early biomarkers of COVID-19 disease severity and mortality.Journal of biomedical optics · 2026Article
- Designing an explainable algorithm based on XGBoost and genetic algorithm for predicting hospitalization needs of COVID-19 patients.Scientific reports · 2026Article
- Artificial intelligence for streamflow prediction in river basins: a use case in Mar Menor.Scientific reports · 2025Article
- Identifying risk factors and predicting long COVID in a Spanish cohort.Scientific reports · 2025Article
- Predictors of Hospitalization for Patients Presenting to Emergency Department with COVID-19 Infection.Journal of clinical medicine · 2025Article
- Article
- Significant association between asthma and a lower risk of mortality among COVID-19 patients in Spain: A meta-analysis.Qatar medical journal · 2024Review
- Identifying Predominant Causes of Death Among Hospitalized COVID-19 Patients During Poland's Second and Third Waves.Medical science monitor : international medical journal of experimental and clinical research · 2023Article
- Predictive Attributes for Developing Long COVID-A Study Using Machine Learning and Real-World Data from Primary Care Physicians in Germany.Journal of clinical medicine · 2023Article
- Investigating the performance of machine learning algorithms in predicting the survival of COVID-19 patients: A cross section study of Iran.Health science reports · 2023Article
- Machine learning algorithms for predicting determinants of COVID-19 mortality in South Africa.Frontiers in artificial intelligence · 2023Article
- Identification of 3 key genes as novel diagnostic and therapeutic targets for OA and COVID-19.Frontiers in immunology · 2023Article
Corrections and comments
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Authors and funding
11 authors at 5 institutions in 2 countries.
Funding
Abstract
The development of tools that provide early triage of COVID-19 patients with minimal use of diagnostic tests, based on easily accessible data, can be of vital importance in reducing COVID-19 mortality rates during high-incidence scenarios. This work proposes a machine learning model to predict mortality and risk of hospitalization using both 2 simple demographic features and 19 comorbidities obtained from 86,867 electronic medical records of COVID-19 patients, and a new method (LR-IPIP) designed to deal with data imbalance problems. The model was able to predict with high accuracy (90-93%, ROC-AUC = 0.94) the patient's final status (deceased or discharged), while its accuracy was medium (71-73%, ROC-AUC = 0.75) with respect to the risk of hospitalization. The most relevant characteristics for these models were age, sex, number of comorbidities, osteoarthritis, obesity, depression, and renal failure. Finally, to facilitate its use by clinicians, a user-friendly website has been developed ( https://alejandrocisterna.shinyapps.io/PROVIA ).
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Registered trials
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