Prognostic Assessment of COVID-19 in the Intensive Care Unit by Machine Learning Methods: Model Development and Validation.

Pan Pan Yichao Li Yongjiu Xiao Bingchao Han Longxiang Su Mingliang Su Yansheng Li Siqi Zhang Dapeng Jiang Xia Chen Fuquan Zhou Ling Ma Pengtao Bao Lixin Xie

Published in: Journal of medical Internet research (2020)

The 8-factor XGBoost model predicts risk of death in ICU patients with COVID-19 well; it initially demonstrates stability and can be used effectively to predict COVID-19 prognosis in ICU patients.

Keyphrases

coronavirus disease
sars cov
machine learning
end stage renal disease
intensive care unit
ejection fraction
newly diagnosed
chronic kidney disease
mechanical ventilation
prognostic factors
peritoneal dialysis
artificial intelligence
respiratory syndrome coronavirus
acute respiratory distress syndrome