Machine Learning Model Predicts COVID-19 Severity, Helps in Decision-Making, Says Study

New York, July 14: A centralised repository of COVID-19 health records built by US researchers, last year, has been helpful in tracing the progression of the disease over time and could eventually be used as the basis for decision-making tools. The National COVID-19 Cohort Collaborative (N3C) is a centralised, harmonised, high-granularity electronic health record repository that is the largest, most representative COVID-19 cohort to date. 'Treatment With Blood Thinners May Reduce Death in COVID-19 Patients', Says Study This multicenter data set can support robust evidence-based development of predictive and diagnostic tools and inform clinical care and policy, said a team of researchers from those including at Universities of Colorado, Michigan, Rochester Medical Center, and Johns Hopkins. The cohort study, published in the JAMA Network, used data from 34 medical centers and included over 1 million adults -- 174,568 who tested positive for COVID-19 and 1,133,848 who tested negative between January 2020 and December 2020. "This cohort study found that COVID-19 mortality decreased over time during 2020 and that patient demographic characteristics and comorbidities were associated with higher clinical severity," said Tellen D. Bennett, from Department of Pediatrics at Colorado's School of Medicine.