Timothy E. Sweeney

The paper identifies a novel framework to quantify immune dysregulation in critical illness by analyzing transcriptomic data across multiple cohorts.

The paper develops a 6-mRNA classifier using non-COVID-19 viral infection data to predict COVID-19 severity, achieving high accuracy in independent cohorts.

The paper integrates transcriptome and clinical data to identify overlooked disease relationships, such as between myositis and interstitial cystitis.

The paper develops gene-expression-based prognostic models for 30-day mortality in sepsis using community-onset and hospital-acquired sepsis cohorts, showing improved prediction when combined with clinical scores.