ArticleDiagnostics (Basel, Switzerland)2022
A Hybrid Feature Selection Approach to Screen a Novel Set of Blood Biomarkers for Early COVID-19 Mortality Prediction.
Article in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Multiscale geographically weighted modeling of tuberculosis incidence in China: integrating geographic perspectives into epidemiological analysis.International journal of health geographics · 2025Article
- Cytokine Profiles as Predictive Biomarkers of Disease Severity and Progression in Engineered Stone Silicosis: A Machine Learning Approach.Diagnostics (Basel, Switzerland) · 2025Article
- A Hybrid Sequential Feature Selection Approach for Identifying New Potential mRNA Biomarkers for Usher Syndrome Using Machine Learning.Biomolecules · 2025Article
- Biomarker states and risk of death among individuals hospitalized with SARS-CoV-2 infection.BMC infectious diseases · 2025Article
- Integrating routine blood biomarkers and artificial intelligence for supporting diagnosis of silicosis in engineered stone workers.Bioengineering & translational medicine · 2024Article
- Functional principal component analysis and sparse-group LASSO to identify associations between biomarker trajectories and mortality among hospitalized SARS-CoV-2 infected individuals.BMC medical research methodology · 2023Article
- MEvA-X: a hybrid multiobjective evolutionary tool using an XGBoost classifier for biomarkers discovery on biomedical datasets.Bioinformatics (Oxford, England) · 2023Article
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3 authors.
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Abstract
The increase in coronavirus disease 2019 (COVID-19) infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has placed pressure on healthcare services worldwide. Therefore, it is crucial to identify critical factors for the assessment of the severity of COVID-19 infection and the optimization of an individual treatment strategy. In this regard, the present study leverages a dataset of blood samples from 485 COVID-19 individuals in the region of Wuhan, China to identify essential blood biomarkers that predict the mortality of COVID-19 individuals. For this purpose, a hybrid of filter, statistical, and heuristic-based feature selection approach was used to select the best subset of informative features. As a result, minimum redundancy maximum relevance (mRMR), a two-tailed unpaired
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