Current knowledge and availability of machine learning across the spectrum of trauma science

Abstract

Machine Learning holds promise for actionable decision support in trauma science, but rigorous proof-of-concept studies are urgently needed. Future research should assess workflow integration, human-machine interaction, and, most importantly, the impact on patient outcome. Machine Learning enhanced causal inference for observational data carries an enormous potential to change trauma research as complement to randomized studies. The scientific trauma community needs to engage with the existing challenges to drive progress in the field.

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