AI-Driven Autonomous Trauma Care: Transforming Emergency Response in Military and Civilian Settings

Introduction: Timely trauma care during the "golden hour" is critical to reducing mortality in military and civilian emergencies. Recent advancements in artificial intelligence (AI), machine learning, and robotics offer new opportunities to improve outcomes through autonomous diagnostics, triage, and logistical coordination. However, there remains a significant gap in integrating these technologies into trauma care systems, particularly in austere or high-pressure environments. Methods: This study conducted a systematic literature review to evaluate the effectiveness of AI-driven autonomous systems in trauma care. Databases searched included PubMed, Scopus, and Web of Science, covering publications from January 2000 to April 2025. Search terms included “AI in trauma care,” “golden hour,” “autonomous medical systems,” and “emergency response.” Grey literature and institutional reports were also analyzed. Study quality was assessed using the Newcastle-Ottawa Scale and AMSTAR tools. Results: AI systems demonstrated high diagnostic accuracy (AUC 0.88–0.92) and significantly improved triage efficiency (e.g., 18.7-minute reduction in wait time). Autonomous evacuation using drones reduced mortality by up to 30%, while rapid surgical handoff was associated with a 66% mortality reduction. Applications in both military and civilian settings showed survival rates exceeding 86%. Key areas enhanced by AI included injury detection, patient prioritization, evacuation logistics, and outcome prediction. Discussion: AI-driven systems enhance each phase of trauma care, particularly within the golden hour. Despite their benefits, challenges remain, including data biases, variable trauma timelines, and ethical considerations. Proposed solutions include the development of offline-capable mobile applications and real-time decision-support tools. Further research is needed to validate AI models and optimize system deployment in resource-limited environments. Conclusion: AI-driven autonomous trauma care systems show substantial promise in improving survival and operational efficiency in both military and civilian emergencies. Integrating these technologies into trauma response protocols may redefine standards for emergency care and significantly reduce preventable deaths.