Building a resilient battlefield medical system for future high-tech warfare: key technologies and global health translation prospects

Traditional battlefield medical systems demonstrate critical vulnerabilities in highly dynamic, high-threat environments, including inadequate survivability, fragmented treatment chains, and ineffective resource coordination, necessitating a fundamental paradigm shift from the perspective of resilience engineering. This study analyzes these deficiencies across four dimensions, namely damage resistance, response speed, intelligent adaptability, and resource synergy, and integrates artificial intelligence, unmanned platforms, and biomedical frontier technologies to develop a resilient medical system architecture. This architecture incorporates modular distributed deployment, intelligent unmanned support, civil-military integration, and dynamic self-evolution. Its core innovation is the closed-loop integration of physical treatment flows and digital information flows. This transforms the support model from static passive response to dynamic autonomous adaptation. When a node is damaged, the information flow automatically re-routes while the physical flow switches to redundant backup routes to ensure continuity of care. A consortium blockchain-based distributed attestation mechanism guarantees tamper-proof, cross-node trusted sharing of casualty data even in communication-denied combat environments. Meanwhile, operational data continuously feeds back into AI models, promoting iterative optimization of resource pre-positioning strategies. Structurally, the extreme constraints faced by battlefield medicine, namely uncertainty, resource scarcity, and time pressure, are highly similar to those in global health emergencies such as natural disasters and disease outbreaks, making our resilience design principles highly transferable to civilian public health rapid-response systems. Although quantitative simulation validation and ethical reviews for certain emerging technologies remain to be improved, the theoretical framework of this resilience system provides a solid analytical foundation for subsequent empirical quantitative evaluation and cross-scenario practical translation.