September 19, 2025Open Access

Management of Severe COVID-19 Diagnosis Using Machine Learning

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This analysis identifies predictive models for COVID-19 severity in 257 patients, highlighting machine learning's role in clinical assessment.

The study achieved high predictive accuracy for COVID-19 severity using machine learning models.
Feature analysis revealed that IL-6 and comorbidity presence strongly correlated with disease severity.
Multiple supervised learning algorithms were evaluated, with ensemble models outperforming traditional ones.
High classification precision was noted in decision tree models, achieving 100% probability in certain severity classes.

Sydorchuk et al. (2025) studied this question.

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This analysis identifies predictive models for COVID-19 severity in 257 patients, highlighting machine learning's role in clinical assessment.