Military Medicine

Deployment process for artificial intelligence applications in radiology practice.

Successful deployment of medical artificial intelligence (AI) systems should start with formulating clear goals and understanding organisational workflows. Comprehensive deployment planning is advised after identifying a suitable product, preliminary testing, and procurement. A structured approach supports effective adoption and improved efficiency. Planning involves evaluating the feasibility of ...

A deep-learning based gait classification and anomaly detection framework for healthcare surveillance.

Gait classification and anomaly detection are non-intrusive approaches that can support healthcare surveillance and clinical gait analysis by identifying abnormal walking patterns. Despite recent advancements, existing methods remain limited by model complexity, high computational requirements, and privacy concerns. This study proposes a unified framework that combines three complementary componen...

Using Artificial Intelligence to Identify Patterns and Predictors of Adverse Drug Reactions in Cardiovascular Patients: A Comprehensive Narrative Review.

Artificial intelligence (AI) has emerged as a transformative tool for improving the detection, prediction, and prevention of adverse drug reactions (A...

An Acceptance Criteria Framework for Determining the Implementation Fit of Custom Large Language Models in Public Health Interventions.

Large language models (LLMs) are increasingly embedded in clinical and population health workflows, including conversational agents such as health cha...

Palliative Care Physicians' Perceptions about Using Artificial Intelligence for Prognostication.

CONTEXT: Statistical and artificial intelligence (AI)-based methods have informed clinical prognostication for decades, evolving into machine learning...

"Check Symptoms & Get Care": Mount Sinai's AI Triage Solution.

Mount Sinai Health System (MSHS), one of New York City's largest academic medical centers, faced a common patient-access challenge: individuals presen...

Bouncing back from stress: objective markers of expressive flexibility and resilience in emergency healthcare workers using computer vision.

Healthcare workers (HCWs) in emergency departments face significant mental health risk due to chronic stressors and repeated trauma, yet symptom under...

Artificial Intelligence in Neonatal Care: The Breadth of Promise, the Depth of Challenge-An Overview.

Artificial intelligence (AI) is becoming an integral tool in clinical care. The recent position statement by the Royal Australasian College of Physici...

Nonverbal AI-Based Communication Robot for Staff in Disaster-Affected Care Facilities: Exploratory ABAB Intervention Study.

BACKGROUND: Medical and welfare facilities in the Noto region of Japan were severely affected by the 2024 Noto Peninsula earthquake and subsequent tor...

A unified multi-modal foundation model for end-to-end emergency care.

Against the backdrop of population aging and the rising burden of chronic diseases in China, emergency departments (EDs) in tertiary hospitals remain ...

High-resolution mapping reveals a profound gap between existing rooftop solar deployment and potential in Africa.

Rooftop photovoltaics offer a flexible and scalable pathway for expanding electricity access and advancing power system transitions in Africa. However...

The role of health literacy and attitudes toward artificial intelligence in the acceptance of telemedicine services among adults in Turkey: a cross-sectional study.

BACKGROUND: The digital transformation in healthcare has led to an increase in the use of telemedicine and artificial intelligence (AI)based applicati...

Digital Management of Early-Onset Type 2 Diabetes: Empowerment, Challenges, and Future Outlook.

PURPOSE OF REVIEW: Early-onset type 2 diabetes (EOT2D), defined as a diabetes diagnosis before 40 years of age, is rising globally and associated with...

Pulmonary nodule prediction in the multi-omics era: integrating radiomics, AI, liquid biopsy, and airway classifiers.

Low-dose CT (LDCT) lung cancer screening significantly reduces mortality but has dramatically increased the detection of pulmonary nodules. Most of th...

Large language model-driven Socratic questioning for endodontic case analysis: A randomised controlled trial.

OBJECTIVE: Endodontic education requires structured clinical reasoning practise, but resource constraints often limit the delivery of case-based instr...

The rise of medical autonomous care, a paradigmatic turning point for military and civilian delivery of health care.

RATIONALE: Resource-limited or austere environments represent a direct threat to the likelihood of survival of patients in need of emergent care. Medi...

Development of a target product profile for artificial intelligence in diabetic eye screening in England: a modified Delphi consensus study.

Artificial intelligence (AI) health-care technologies offer a means of addressing the growing gap between health-care capacity and demand. However, fe...

Injury prediction in elite women's football: an integrative machine learning-based decision-support framework.

Injuries in elite sports disrupt team performance, shorten careers, and incur significant financial costs, highlighting the critical need for accurate...

Bioactive environments to combat antimicrobial resistance: artificial intelligence and model-driven microbial biocontrol for living materials.

Antimicrobial resistance (AMR) continues to outpace development of new therapeutics. Many interventions focus on treating infection after it occurs, b...

Bridging the global Parkinson's divide: Technology as a structural solution for equitable and brain health-integrated care.

Parkinson's disease (PD) is the fastest-growing neurodegenerative disorder worldwide, with projections exceeding 25 million people by 2050. Its burden...