Artificial intelligence in trauma care: applications, ethical challenges, and pathways toward responsible integration

Abstract

PURPOSE OF REVIEW: Artificial intelligence is increasingly applied across the trauma care continuum, from prehospital triage to in-hospital decision-making. This review provides a timely synthesis of emerging applications, ethical challenges, and regulatory frameworks shaping the responsible integration of artificial intelligence into trauma systems. RECENT FINDINGS: Recent studies highlight the potential of machine learning and deep learning models to improve trauma triage accuracy, imaging interpretation, and prediction of hemorrhage and transfusion needs. Despite promising accuracy, most systems remain in proof-of-concept phases with limited external validation. Ethical and governance challenges - particularly regarding data privacy, transparency, accountability, and automation bias - remain major barriers to clinical translation. The WHO guidance on artificial intelligence ethics and the European Union Artificial Intelligence Act establish core principles of safety, fairness, and human oversight, framing the foundation for trustworthy implementation. SUMMARY: Artificial intelligence offers transformative opportunities for trauma care but requires rigorous validation, transparent governance, and structured clinician training to ensure safe, equitable, and ethically aligned deployment. Responsible, human-centered integration - anchored in oversight, algorithmic stewardship, and interdisciplinary collaboration - will be key to realizing full potential of artificial intelligence in trauma medicine.

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