Military Medicine

Federated Learning in Healthcare: From Research to Real-World Deployment.

Artificial intelligence (AI), including deep and traditional machine learning, holds great promise for advancing biomedical research and healthcare. However, most AI studies remain academic in nature and rarely transition into clinical practice, largely due to limited access to diverse real-world datasets. Centralized learning, the traditional approach to multi-institutional collaboration, is hind...

Adapting quality function deployment to translate patient feedback into prioritized technical requirements for healthcare artificial intelligence.

Human-centered artificial intelligence (AI) is increasingly recognized as important to advancing quality, safety, and trust in healthcare analytics, yet most validation frameworks continue to prioritize technical metrics over interpretability and stakeholder experience. Quality Function Deployment (QFD) offers a systematic method for translating customer requirements into technical design, but its...

To see or not to see the vet: A vignette-based study of decision-making by UK dog owners regarding seeking veterinary care for commonly presenting conditions.

Barriers to accessing veterinary-care for dog-owners are diverse and dynamic, and widely accepted as major canine welfare threats because of potential...

Biometric Data in Post-Traumatic Stress Disorder Detection: A Scoping Review of Digital Health Applications.

CONTEXT: Post-traumatic stress disorder (PTSD) is mainly assessed through self-reports and clinician interviews, which can delay recognition and limit...

The balance between artificial and human intelligence in clinical practice.

INTRODUCTION: Artificial intelligence (AI) is becoming increasingly integrated into clinical care in hand surgery. Its applications extend across diag...

The Role of AI in Improving Digital Wellness Among Older Adults: Comparative Bibliometric Analysis.

BACKGROUND: Advances in artificial intelligence (AI) have revolutionized digital wellness by providing innovative solutions for health, social connect...

Initial diagnosis and management of acute ischemic stroke: recent update and future direction.

Acute ischemic stroke (AIS) outcomes depend critically on rapid, accurate early diagnosis in the emergency department. Traditional prehospital tools a...

Development and deployment of an interpretable stacking ensemble model for predicting in-hospital mortality in ICU patients with chronic kidney disease and sepsis.

OBJECTIVE: To develop an interpretable stacking ensemble model for predicting in-hospital mortality in intensive care unit (ICU) patients with CKD and...

Unlocking the potential of Artificial Intelligence: A guideline for deployment.

The rapid development of Artificial Intelligence technology and digital tools is becoming pivotal to advancing healthcare. AI technology has demonstra...

Artificial intelligence and machine learning in antimicrobial discovery, resistance prediction, and precision therapy.

OBJECTIVES: The global crisis of antimicrobial resistance (AMR) demands a paradigm shift in traditional drug discovery, and artificial intelligence (A...

Predicting emergency mortality risk in traumatic brain injury: comparative analysis of machine learning and large language model GPT-5.

BACKGROUND: Artificial intelligence (AI) has become increasingly important in predicting outcomes of traumatic brain injury (TBI). Traditional machine...

AI-powered detection of dental anatomy: a YOLO-based approach.

OBJECTIVE: This study aims to develop an AI-powered detection system for identifying dental anatomy-specifically tooth numbers and names-using YOLO (Y...

Development and validation of machine learning models to predict PTSD at multiple time points in hospitalized trauma patients.

BACKGROUND: Posttraumatic stress disorder (PTSD) is a severe trauma-related mental disorder with high global burden. Early identification remains chal...

Precision prediction of posttraumatic stress disorder symptom surges: A pilot study integrating real-time daily data with supervised learning.

The application of machine learning algorithms to daily diary data represents a valuable tool for improving dynamic prediction of posttraumatic stress...

Vision-language models in diagnostic imaging: review of technical advances, clinical validation, and practical deployment.

BACKGROUND: Radiology faces an unprecedented workload crisis, creating demand for AI solutions to enhance efficiency and quality. Vision-language mode...

Cardiac Rehabilitation for Coronary Artery Disease: Gaps, Digital Models, and the Future of Personalized Prevention.

Cardiovascular disease is the leading cause of global morbidity and mortality, with coronary artery disease representing the primary driver of prematu...

Advances in the Application of Digital Health Technologies in the Management of Patients With Inflammatory Bowel Disease.

Inflammatory bowel disease (IBD) is a chronic disorder that requires long-term follow-up and individualized management. With the rapid development of ...

Innovation, Technology, and Telemedicine in Critical Care.

Critical care medicine is undergoing a major transformation driven by rapid technological innovation, digital integration, and telemedicine. This arti...

ProSocial Artificial Intelligence in Oral Health: A Paradigm Shift.

This article examines the transformative potential of ProSocial Artificial Intelligence (AI) in revolutionizing oral health care. ProSocial AI emphasi...

Increased Utilization of Telemedical Emergency and Nonurgent Care Following Deployment of Virtual Triage and Care Referral in Australia.

OBJECTIVE: To evaluate whether an artificial intelligence-based national virtual triage and care referral (VTCR) service in Australia improved care ac...