Military Medicine

[Emerging classifications of cardiometabolic risk in obesity].

Obesity, historically defined by body mass index and waist circumference, is a major risk factor for cardiometabolic complications; however, these indicators do not capture the phenotypic heterogeneity or the underlying pathophysiology. Adipose dysfunction, characterized by hypertrophy, chronic inflammation, and ectopic lipid deposition, promotes insulin resistance, lipotoxicity, and vascular abno...

Research on the adaptation path of corporate strategy based on the differences in AI governance visions between the Atlantic and China.

Strategic adaptation to divergent AI governance regimes is increasingly central to multinational corporate strategy. Regulatory divergence across the European Union, United States, and China has moved AI governance from a compliance function to a strategy-shaping constraint, yet firm-level adaptation evidence remains disproportionately conceptual and fragmented by single-jurisdiction perspectives....

[Clinical practice guidelines for the application of intelligent technology in spinal surgery (2026 edition)].

In response to the challenges of insufficient precision and limited safety associated with traditional techniques in the diagnosis and treatment of co...

Lightweight deep learning model for nonconvulsive status epilepticus diagnosis using EEG time-frequency analysis.

Nonconvulsive Status Epilepticus (NCSE) is a persistent epileptic seizure state whose detection primarily relies on visual EEG inspection. Automated a...

Parallel AI-driven framework for post-quantum secure medical image communication using swin-transformer restoration.

Reliable and secure transmission of medical images is essential for telemedicine, remote diagnosis, and distributed healthcare systems. However, medic...

Integrating AI into hospital workflows: implementation strategies and real-world barriers.

Artificial intelligence (AI) is increasingly being integrated into hospital systems with the potential to transform clinical workflows, operational ef...

National Collaboration on AI Deployment in Norway.

In Norway, a national AI platform for radiology was introduced to support coordinated procurement, deployment, and scaling across all health regions. ...

Aligning AI-Native 6G Healthcare Systems with EU Ethical and Legal Frameworks.

The convergence of AI, robotics, and 6G networks is reshaping healthcare through real-time This paper applies a structured regulatory-technical analys...

Generative AI in Healthcare Solutions: A Review of Opportunities and Challenges.

The integration of Generative Artificial Intelligence (GenAI) into eHealth represents a transformative shift in the design, development, and deploymen...

The Evolving Utility of Artificial Intelligence-Based Tools for the Detection of Heart Failure and Cardiomyopathies: From Potential to Implementation.

PURPOSE OF REVIEW: Artificial intelligence (AI) is poised to transform heart failure (HF) care across the clinical continuum, yet a substantial gap re...

Mixed Reality and Desktop Hand Hygiene Training with Deep Learning-Based Step Recognition and Real-Time Decision Support.

Hand hygiene (HH) is essential for preventing healthcare-associated infections, yet conventional monitoring approaches primarily capture event occurre...

Large Language Models in Colorectal Cancer Care and Clinical Decision Support: Systematic Review.

BACKGROUND: Colorectal cancer (CRC) is a leading cause of cancer morbidity and mortality worldwide. The complexity of guideline-concordant care and un...

Post-swallowing voice-based aspiration screening in dysphagia using a deep learning approach: insights from audio segmentation.

Dysphagia presents a serious risk of aspiration that requires continuous monitoring. This study introduces standardized 2 s voice segments for aspirat...

Large Language Models in Clinical Trial Recruitment: Sociotechnical and Economic Framework Development Study.

BACKGROUND: Large language models (LLMs) have shown substantial promise in patient-trial matching, but most published studies still evaluate the perfo...

Systematic review and meta-analysis of machine learning models predicting massive hemorrhage protocol in trauma.

Timely activation of massive hemorrhage protocols (MHP) is critical to prevent exsanguination and improve survival in trauma patients. Current clinica...

Optimizing AI implementation for surgery: recommendations for infrastructure and deployment in the operating room.

Recent years have seen a surge in the development of Artificial Intelligence (AI) technologies to enhance intraoperative decision-making and improve p...

Development of colorimetric and machine learning based accurate glucose detection platform for point of care applications.

Improving overall health and preventing complications is crucial for timely and effective treatment of diabetes patients. In this direction, accurate ...

Multisource Machine Learning Model for Detecting Referral-Warranted Retinopathy of Prematurity.

PURPOSE: To develop a multisource machine learning model for detecting referral-warranted retinopathy of prematurity (RW-ROP) using retinal images and...

Multicenter validation and randomized crossover reader evaluation of deep learning-assisted tri-sequence three-dimensional MRI segmentation for hypopharyngeal tumor.

BACKGROUND AND PURPOSE: Accurate MRI-based target delineation for hypopharyngeal squamous cell carcinoma (HPSCC) is clinically important but expertise...

Detection of Posttraumatic Stress Disorder With Rest-Activity Data: Machine Learning Approach Using Wearable and Self-Report Data.

BACKGROUND: Growing evidence suggests that disruptions in rest-activity rhythms may serve as relevant markers of posttraumatic stress disorder (PTSD)....