COVID-19 severity analysis for clinical decision support based on machine learning approach.

ABSTRACT: The COVID-19 pandemic has placed immense pressure on global healthcare systems, underscoring the urgent need for early and accurate prediction of disease severity to improve patient care and optimize resource allocation. Failure in ward allocation can lead to wasted hospital resources and inadequate treatment. This study analyzes data from 806 COVID-19 patients admitted to the emergency room of Chungbuk National University Hospital, Korea, between January 2021 and December 2022, to develop machine learning models that predict which patients should be prioritized for intensive care unit (ICU) placement based on initial clinical information. Additionally, two different severity criteria were considered based on actual ICU level interventions (Criterion I) and based on national policy definit

SUBMITTER: Kim JE 

PROVIDER: S-EPMC12686474 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature