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Research team creates statistical model to predict COVID-19 resistance Proof-of-concept study shows promise for machine-learning system that uses electronic health data to make its predictions "If we can identify which people are naturally able to avoid infection by SARS-CoV-2, we may be able to learn -- in addition to societal and behavioral factors -- which genetic and environmental differences influence their defense against the virus," says lead study author Karen (Kai-Wen) Yang, a biomedical engineering graduate student in the Translational Informatics Research and Innovation Lab at The Johns Hopkins University. "That insight could lead to new preventive measures and more highly targeted treatments." For its study, the research team set out to determine if a machine-learning statistical model could use health characteristics stored in electronic health records -- providing patient data such as comorbidities (other medical conditions) and prescribed medication...