Clinical severity classes in COVID-19 pneumonia have distinct immunological profiles, facilitating risk stratification by machine learning.

Laura Wiffen,Leon Gerard D'Cruz,Thomas Brown, Tim W Higenbottam,Jonathan A Bernstein, Courtney Campbell,Joseph Moellman,Debajyoti Ghosh, Clive Richardson, Wynne Weston-Davies,Anoop J Chauhan

Frontiers in immunology（2023）

引用 0|浏览4

暂无评分

摘要

Distinct immunological fingerprints from serum biomarkers exist within different severity classes of COVID-19, and harnessing them using machine learning enabled the development of clinically useful triage and prognostic tools. Complement-mediated lung injury plays a key role in COVID-19 pneumonia, and preliminary results hint at the usefulness of a C5 inhibitor in COVID-19 recovery.

查看译文

关键词

pneumonia,distinct immunological profiles,clinical severity classes,risk stratification

AI 理解论文

溯源树

样例

生成溯源树，研究论文发展脉络

Chat Paper

正在生成论文摘要