Prognostic Model of ICU Admission Risk in Patients with COVID-19 Infection Using Machine Learning.

ABSTRACT: With the onset of the COVID-19 pandemic, the number of critically sick patients in intensive care units (ICUs) has increased worldwide, putting a burden on ICUs. Early prediction of ICU requirement is crucial for efficient resource management and distribution. Early-prediction scoring systems for critically ill patients using mathematical models are available, but are not generalized for COVID-19 and Non-COVID patients. This study aims to develop a generalized and reliable prognostic model for ICU admission for both COVID-19 and non-COVID-19 patients using best feature combination from the patient data at admission. A retrospective cohort study was conducted on a dataset collected from the pulmonology department of Moscow City State Hospital between 20 April 2020 and 5 June 2020. The datas

SUBMITTER: Islam KR 

PROVIDER: S-EPMC9498213 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature