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Fig. 1 | Critical Care

Fig. 1

From: Real-time machine learning model to predict short-term mortality in critically ill patients: development and international validation

Fig. 1

The area under the receiver operating characteristic curves for the cohorts. The label “iMORS” denotes our model, while the remaining models listed serve as comparisons. A internal validation on SNUH testing dataset B external validation on MIMIC C external validation on eICU-CRD (D) external validation on AmsterdamUMCdb. SNUH Seoul national university hospital, MIMIC Medical information mart for intensive care, eICU-CRD eICU collaborative research database, AmsterdamUMCdb Amsterdam university medical center database, SPTTS single-parameter weighted “track and trigger” systems, NEWS national early warning score, MEWS modified early warning score, APACHE acute physiology and chronic health evaluation, SAPS simplified acute physiology score, SOFA sequential organ failure assessment, AUROC area under the receiver operating characteristic, sen sensitivity, spec specificity

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Critical Care

ISSN: 1364-8535