A generative transformer trained on tokenized patient histories can be repurposed as a dynamic early-warning system, outperforming standard clinical scores and tabular baselines on MIMIC-IV emergency department predictions.
Managing emergency department crowding through improved triaging and resource allocation
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Foundation Model of Electronic Medical Records for Adaptive Risk Estimation
A generative transformer trained on tokenized patient histories can be repurposed as a dynamic early-warning system, outperforming standard clinical scores and tabular baselines on MIMIC-IV emergency department predictions.