Military Medicine

A Scoping Review of Digital Behavioral Approaches to Improve Medication Adherence in Type 2 Diabetes.

PURPOSE OF REVIEW: Consistent medication adherence is fundamental for achieving favorable health outcomes in diabetes care; however, attaining optimal adherence remains a challenge. This review summarized recent evidence on digital behavioral interventions designed to improve medication adherence in type 2 diabetes (T2D) and identified key components commonly incorporated in these interventions. R...

Dual-Approach AI for Pediatric Supracondylar Fractures: Multiclass Radiograph Classification with Explainable AI and Diagnostic Meta-analysis of AI-Based Computational Approaches.

RATIONALE AND OBJECTIVES: Pediatric supracondylar fractures (SCFs) are the most common elbow injury in children, yet radiographic diagnosis remains challenging due to complex developmental anatomy, with initially missed fracture rates of 17-77%. Prior artificial intelligence (AI) studies have been limited to binary classification frameworks without Gartland subtype differentiation, and no diagnost...

From Clinic to Home: Validating the Social Communication Scale for Telemedicine-Supported Early Autism Screening in Chinese Toddlers.

Telemedicine is reshaping how early autism detection can be delivered, particularly in resource-limited settings. Yet, most existing tele-assessment t...

Harmonizing complexity and efficiency: Helix Fusion HarmonyNet's breakthrough in EEG-based postoperative delirium recognition.

Postoperative delirium (POD) is a common perioperative complication involving central nervous system dysfunction, particularly among critically ill an...

Overcoming barriers to neurosurgical care with technology and innovation.

Technological advancements show great potential in transforming and advancing global surgery. Compared to general medicine, technology in neurosurgery...

From assistant to collaborator: A systematic review of the evolution of artificial intelligence in end-stage renal disease care and management.

We aimed to systematically analyze the historical evolution of artificial intelligence (AI) in end-stage renal disease (ESRD) management and propose a...

Assessing digital health curriculum needs: a mixed-methods study of student and faculty perspectives in a Singapore medical school.

BACKGROUND: The rapid advancement of digital technologies has transformed healthcare delivery, creating an imperative for medical education to integra...

Ethical Considerations on Artificial Intelligence, Health and Health Care. All That Glisters Is Not Gold.

BACKGROUND: Artificial intelligence (AI) is transforming global health care through innovations in deep learning, generative models and agentic AI sys...

Machine learning-enabled chemical ecology for integrated pest management: from volatiles to field applications.

Machine learning is transforming chemical ecology by accelerating the discovery and deployment of semiochemical-based tools for precision pest managem...

Electrocardiogram Abnormality Classification From Summary Statistics With Patient-Level Validation and Process-Focused Evaluation.

BACKGROUND: Machine learning (ML) applications in clinical medicine are vulnerable to data leakage, particularly temporal leakage from post-diagnostic...

Evaluating the Accuracy, Empathy, and Readability of Generative AI Versus Registered Nurses in Discharge Planning: A Vignette-Based Study.

AIM: To compare the multidimensional performance of discharge instructions generated by generative AI (GPT-4) versus those created by clinical registe...

The Digital Transformation of Rehabilitation Medicine: A Narrative Review of Artificial Intelligence Innovations, Clinical Integration, and Future Paradigms.

BACKGROUND: Traditional rehabilitation medicine, primarily dependent on qualitative clinical assessment and static therapeutic protocols, faces signif...

A strategic pathway for the ethical development of AI tools in dementia care.

Artificial intelligence (AI) is rapidly entering dementia clinical practice, offering opportunities across the care continuum. However, cognitive decl...

Detecting short-term post-traumatic stress disorder symptom increases among veterans: machine-learning analysis integrating wearable sensor and daily self-report data.

BACKGROUND: Post-traumatic stress disorder (PTSD) symptoms can fluctuate substantially over short periods, yet routine screening typically relies on i...

Integrating Microfluidics Chips into Vector-Borne Disease Surveillance: Technological Breakthroughs and Persistent Hurdles.

BACKGROUND: Vector-borne diseases (VBDs), such as malaria, dengue, and Zika virus infections, remain a critical global health burden, particularly in ...

Spatial synaptic pruning mechanism of NAC microglia in differential regulation of PTSD- and depression-like behaviors.

BACKGROUND AND AIMS: Post-traumatic stress disorder (PTSD) comorbid with depression is a prevalent, treatment-refractory clinical syndrome. Emerging e...

Visual Signal Typing in Voice Assessment: A Systematic Review of Methods, Reliability, and Clinical Applications.

Acoustic analysis is a fundamental step in the multidimensional assessment of dysphonia. However, conventional perturbation measures require nearly pe...

Detecting Incisional Surgical Site Infections on Wound Images Through Deep Learning.

IMPORTANCE: Surgical site infections (SSIs) are common postoperative complications, often detected after patients leave the hospital, especially in ti...

Bayesian Analysis of AI-Driven Cost Savings in UK and Australian Health Care Systems: Cross-Sector Implementation Study.

BACKGROUND: Health care systems face growing fiscal pressure while AI reaches clinical parity in several domains. UK National Health Service expenditu...

An Umbrella Review of Artificial Intelligence Applications in Mental Health Care.

BACKGROUND: Artificial intelligence (AI) is increasingly used in mental health care to address rising demand, workforce shortages and access barriers;...