Application of machine learning approach in emergency department to support clinical decision making for SARS-CoV-2 infected patients.

ABSTRACT: To support physicians in clinical decision process on patients affected by Coronavirus Disease 2019 (COVID-19) in areas with a low vaccination rate, we devised and evaluated the performances of several machine learning (ML) classifiers fed with readily available clinical and laboratory data. Our observational retrospective study collected data from a cohort of 779 COVID-19 patients presenting to three hospitals of the Lazio-Abruzzo area (Italy). Based on a different selection of clinical and respiratory (ROX index and PaO2/FiO2 ratio) variables, we devised an AI-driven tool to predict safe discharge from ED, disease severity and mortality during hospitalization. To predict safe discharge our best classifier is an RF integrated with ROX index that reached AUC of 0.96. To predict disease sev

SUBMITTER: Casano N 

PROVIDER: S-EPMC10561065 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature