A fused tabular-textual transformer modestly improves early pediatric cardiac arrest prediction on four of five metrics in a private CICU cohort, but not on AUROC.
Prognostic accuracy of machine learning models for in-hospital mortality among children with phoenix sepsis admitted to the pediatric intensive care unit,
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Early Risk Prediction of Pediatric Cardiac Arrest from Electronic Health Records via Multimodal Fused Transformer
A fused tabular-textual transformer modestly improves early pediatric cardiac arrest prediction on four of five metrics in a private CICU cohort, but not on AUROC.