Personalized and real time hemodynamic management in critical care using Dynamic Cohort Ensemble Learning (DynaCEL).

ABSTRACT: Effective hemodynamic management in the intensive care unit requires individualized targets that adapt to dynamic clinical conditions. We developed Dynamic Cohort Ensemble Learning (DynaCEL), a real-time framework that recommends personalized heart rate and systolic blood pressure targets by modeling each time point post-intensive care unit admission as a distinct temporal cohort. Trained on eICU data and validated on MIMIC-IV and Indiana University Health datasets, DynaCEL demonstrated robust predictive performance (AUCs 0.83-0.91). In the MIMIC-IV cohort, proximity to DynaCEL-predicted targets was associated with lower 24-hour mortality compared to fixed targets, after adjustment using propensity score matching. Dose-response and comparative analyses revealed that greater deviations from

SUBMITTER: Meng L 

PROVIDER: S-EPMC12290091 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature