This study explores the use of AI and machine learning (ML) to stratify COVID-19 patients based on omics data and clinical biomarkers. The researchers developed ML models that predict COVID-19 severity and survival using clinical features, achieving high accuracy. Model explainability analysis identified key biomarkers associated with severe cases and reduced survival, which were further validated by external studies. Weighted gene co-expression network analysis provided insights into gene networks associated with COVID-19 severity and clinical features. The findings highlight the potential of AI/ML for personalized medicine in COVID-19 and other viral infections.
Publisher
International Journal of Molecular Sciences
Published On
Mar 26, 2023
Authors
Babatunde Bello, Yogesh N Bundey, Roshan Bhave, Maksim Khotimchenko, Szczepan W Baran, Kaushik Chakravarty, Jyotika Varshney
Tags
AI
machine learning
COVID-19
biomarkers
personalized medicine
omics data
severity prediction
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