Autonomous and Artificial Intelligence-Enabled Drone Systems for Medical Triage: A State-of-the-Art Review of Emerging Technologies and Swarm Applications

Mass casualty incidents (MCIs) demand rapid, accurate triage to prioritize patient care and allocate limited resources. In recent years, the convergence of unmanned aerial vehicles (UAVs), swarm intelligence, biosensing, and artificial intelligence (AI) has introduced a transformative possibility: autonomous airborne triage. This state-of-the-art narrative review examines 14 recent studies (2019–2025) at the intersection of drone swarms, vital signs monitoring, and AI-driven classification systems. The findings reveal a field in its early stages, dominated by simulations, conceptual frameworks, and prototype evaluations, with limited translation into real-world deployment. Notably, several studies demonstrate the technical feasibility of using swarm-coordinated UAVs for real-time triage based on posture recognition, respiratory metrics, and consciousness assessment. However, persistent challenges remain, including limited field validation, ethical concerns over decision-making autonomy, and the absence of robust regulatory standards. As recent military conflicts have accelerated drone development through rapid iteration and urgent necessity, a similar shift in the medical domain may soon emerge, provided that technological progress is matched by interdisciplinary cooperation, ethical foresight, and clinical integration. This review highlights the critical need for human-centered design, context-aware algorithms, and hybrid operational models that balance machine autonomy with expert oversight. Swarm-based UAV triage systems, if responsibly developed and field-tested, could redefine the speed, safety, and precision of global emergency response.