互操作性
医疗保健
文档
计算机科学
过程管理
工程管理
计算机安全
业务
工程类
政治学
操作系统
程序设计语言
法学
作者
Zachary William Riggenbach,John Van Eaton,A. V. Kelly,Ha Eun Kim,Jason Bingham
标识
DOI:10.1093/milmed/usaf165
摘要
ABSTRACT Background Artificial Intelligence (AI) has become a key component of the U.S. Army Medical Modernization Strategy, which seeks to enhance military health care through innovative technologies. Within the Military Health System (MHS), AI applications in diagnostics, patient monitoring, logistical support, and trauma management are under active exploration. Applications Key initiatives include AI-driven telementoring, decision support tools, automated trauma documentation, and remote patient monitoring. These technologies aim to improve care delivery and operational efficiency in combat zones, particularly during mass casualty incidents and in resource-limited environments. Challenges Implementation faces significant obstacles, including the need for robust data collection methods, secure and interoperable storage solutions, and frameworks to address ethical and trust issues. Decentralized storage technologies, such as blockchain, and explainable AI systems are proposed to enhance reliability and transparency. Strategic Considerations Advancements by near-peer adversaries, such as China and Russia, in AI-driven military health care underscore the urgency for the United States to accelerate its integration efforts. The U.S. Army Medical Modernization Strategy emphasizes interagency collaboration and targeted research as critical components for maintaining a strategic edge. Conclusion Artificial Intelligence–driven automation offers a transformative pathway for military trauma care, enabling enhanced efficiency and resilience. Addressing implementation barriers and aligning efforts with the U.S. Army Medical Modernization Strategy are essential to ensure operational superiority and improved survival outcomes on the battlefield.
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