Characterising risk of in-hospital mortality following cardiac arrest using machine learning: A retrospective international registry study.

ML approaches significantly enhance predictive discrimination for mortality following cardiac arrest compared to existing illness severity scores and LR, without the use of pre-hospital data. The discriminative ability of these ML models requires validation in external cohorts to establish generalisability.