An AI-powered patient triage platform for future viral outbreaks using COVID-19 as a disease model.

ABSTRACT: Over the last century, outbreaks and pandemics have occurred with disturbing regularity, necessitating advance preparation and large-scale, coordinated response. Here, we developed a machine learning predictive model of disease severity and length of hospitalization for COVID-19, which can be utilized as a platform for future unknown viral outbreaks. We combined untargeted metabolomics on plasma data obtained from COVID-19 patients (n = 111) during hospitalization and healthy controls (n = 342), clinical and comorbidity data (n = 508) to build this patient triage platform, which consists of three parts: (i) the clinical decision tree, which amongst other biomarkers showed that patients with increased eosinophils have worse disease prognosis and can serve as a new potential biomarker with h

SUBMITTER: Charkoftaki G 

PROVIDER: S-EPMC10463861 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature