  Respiratory failure is the one of major causes of death in critical care
unit. During the outbreak of COVID-19, critical care units experienced an
extreme shortage of mechanical ventilation because of respiratory failure
related syndromes. To help this, the early mortality risk prediction in
patients who suffer respiratory failure can provide timely support for clinical
treatment and resource management. In the study, we propose a dynamic modeling
approach for early mortality risk prediction of the respiratory failure
patients based on the first 24 hours ICU physiological data. Our proposed model
is validated on the eICU collaborate database. We achieved a high AUROC
performance (80-83%) and significantly improved AUCPR 4% on Day 5 since ICU
admission, compared to the state-of-art prediction models. In addition, we
illustrated that the survival curve includes the time-varying information for
the early ICU admission survival analysis.
