Document Type : Review
Authors
1
Nursing and Midwifery Care Research Center, Department of Critical Care Nursing, School of Nursing & Midwifery, Tehran University of Medical Sciences, Tehran, Iran
2
Tissue Engineering and Regenerative Medicine Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran
3
Chemical Injuries Research Center, Systems Biology and Poisoning Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
4
College of Nursing, Gulf Medical University, United Arab Emirates
5
Nursing department, Nursing Faculty, Baqiyatallah University of Medical Sciences, Tehran, Iran.
Abstract
Background and Aim: Military medicine operates within uniquely complex and resource-constrained environments, where rapid, precise, and adaptive healthcare delivery is critical. Artificial intelligence (AI), leveraging advanced computational models and data-driven algorithms, offers transformative potential to enhance clinical decision-making, operational efficiency, and logistical support in these high-stakes settings. This narrative review critically examines the current and emerging applications of AI in military medicine, focusing on technological innovations, ethical imperatives, and operational challenges to provide a comprehensive and authoritative synthesis.
Methods: A systematic narrative review was conducted by querying multidisciplinary databases including PubMed, Scopus, and Web of Science. Search strategies combined AI-specific terminologies (e.g., machine learning, deep learning, natural language processing) with military medicine contexts (e.g., combat casualty care, telemedicine, medical robotics). Inclusion criteria encompassed peer-reviewed studies, government white papers, and expert consensus documents published up to April 1, 2025. Dual independent screening and full-text review yielded 65 rigorously selected sources. The PRISMA 2020 framework guided the review process.
Results: The applications of artificial intelligence in military medicine encompass prevention, battlefield diagnostics, automated triage, robotic-assisted surgery, mental health analytics, predictive logistics, immersive training simulations, and rehabilitation. Key technological advances include convolutional neural networks for trauma imaging, reinforcement learning for casualty prioritization, AI-enabled biosurveillance, and generative AI for scenario-based training. These innovations have demonstrated improvements in diagnostic accuracy, operational responsiveness, and resource optimization under combat conditions. While AI offers substantial benefits, its integration necessitates stringent safeguards addressing data privacy, algorithmic bias, and the preservation of human-in-the-loop oversight. Ethical frameworks and comprehensive education programs are critical to ensure responsible deployment and to foster trust among military healthcare providers.
Conclusion: AI represents a pivotal enabler for advancing military medical capabilities. Realizing its full potential requires interdisciplinary collaboration, robust ethical governance, and continuous innovation tailored to the operational complexities of military healthcare environments.
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