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

Area of Science:

• Medical Informatics
• Artificial Intelligence in Healthcare
• Trauma Surgery

Background:

• Artificial intelligence is increasingly utilized across the entire spectrum of trauma care.
• Applications range from prehospital patient triage to critical in-hospital decision-making processes.

Purpose of the Study:

• To synthesize emerging applications of artificial intelligence in trauma care.
• To review the ethical challenges associated with AI implementation.
• To examine regulatory frameworks for responsible AI integration into trauma systems.

Main Methods:

• Systematic review of recent studies on artificial intelligence in trauma care.
• Analysis of machine learning and deep learning models for trauma applications.
• Examination of ethical guidelines and regulatory acts (e.g., WHO, EU AI Act).

Main Results:

• Machine learning and deep learning models demonstrate potential in improving trauma triage, imaging interpretation, and predicting hemorrhage/transfusion needs.
• Most AI systems are currently in proof-of-concept stages with limited external validation.
• Key barriers to clinical translation include data privacy, transparency, accountability, and automation bias.

Conclusions:

• Artificial intelligence presents transformative potential for trauma care delivery.
• Rigorous validation, transparent governance, and clinician training are essential for safe and equitable AI deployment.
• Human-centered integration, emphasizing oversight and collaboration, is vital for realizing AI's full potential in trauma medicine.