Military Medicine

SqueakPose Studio, an end-to-end platform for pose estimation and real-time edge-AI deployment.

Accurate pose estimation underpins quantitative analysis of behavior, yet many deep learning-based tracking tools remain optimized for offline workflows that rely on fragmented software pipelines, workstation-grade GPUs, or external middleware to enable real-time deployment. Here, we present an integrated software-hardware ecosystem for pose estimation that spans dataset creation, model training, ...

Achieving Equity in Generative Artificial Intelligence in Cardiovascular Medicine.

Artificial intelligence (AI), specifically generative AI, presents opportunities to advance equity through transformative practices in cardiovascular care. In this review, we describe how generative AI models risk perpetuating inequities through representation bias, measurement and labeling bias, deployment bias, and contextual issues. We propose a framework for equitable generative AI that addres...

Artificial intelligence assisted telemedicine, clinical decision support for anesthesia and critical care in intensive care units: a scoping review.

BACKGROUND: Artificial intelligence (AI) has been increasingly used in care delivery in intensive care units (ICUs) and anesthesia-critical care pract...

Attitudes and Needs of Health Care Providers Toward Artificial Intelligence-Assisted Pediatric Palliative Care: Mixed Methods Study.

BACKGROUND: While artificial intelligence's (AI's) transformative potential in health care is widely acknowledged, its application in highly sensitive...

Expatriate health care workers in Saudi Arabia: Exploring workforce integration, advantages, and challenges in a globalized health care system.

BACKGROUND: Effective expatriate management has become crucial in the health care sector, driven by the growing number of globally mobile professional...

Development and validation of a dual-channel deep learning for continuous acute kidney injury prediction in critically ill patients.

This study aimed to develop and externally validate a real-time, continuous prediction model for 48-h acute kidney injury (AKI) risk in critically ill...

TRUST: an large language model-based dialogue system for trauma understanding and structured assessments.

OBJECTIVES: While large language models (LLMs) have been widely used to assist clinicians and support patients, no existing work has explored dialogue...

Advances in Remote Monitoring Technology Applications in Anesthesia: A Narrative Review.

The swift progress of digital and sensor technologies is hastening the incorporation of remote monitoring into anesthesiology. While several reviews h...

AI in clinical diagnostics in dermatology: applications, validation, and real-world use cases.

Artificial intelligence (AI) has moved from proof-of-concept studies in dermatology to selective, real-world clinical use, particularly in image-based...

Predictive analytics and risk stratification models in internal medicine: from risk scores to real-time machine learning.

Internal medicine involves high-stakes, time-sensitive decisions (such as triaging acute illnesses, escalating care, providing thromboprophylaxis, pla...

Impact of feature engineering on predicting non-contact football injuries.

Non-contact injuries in professional football impose significant performance and economic burdens, yet the influence of workload feature representatio...

Survivor Perspectives on Artificial Intelligence Integration in Breast Cancer Treatment: A Qualitative Study of Trust, Equity, and Application.

FUNDING: Funding (NIH #1OT2OD037972-01). OBJECTIVE: Artificial intelligence (AI) may enhance the efficiency and personalization of breast cancer (BC) ...

Clinical artificial intelligence (AI) in Japan: Regulatory pathways, domain-specific evidence, and its data infrastructure from an international perspective.

Artificial intelligence (AI) has advanced rapidly across clinical domains, generating both a growing evidence base and dedicated regulatory frameworks...

Reference Standards, Numerical Consistency, and Scoring Logic: Pre-deployment Assurance Considerations for AI-Assisted Third Molar Extraction Planning : Regarding: Ko J, Sooksatra S, Kim S, Tang S, Ha JE, Han DH, Lee KH, Jung YJ, Kim MJ. Quantitative assessment of third molar extraction difficulty and nerve injury risk using artificial intelligence and image processing. Ann Biomed Eng. 2026. https://doi.org/10.1007/s10439-026-04114-9.

A Futures Framework for Clinical AI Governance: Anticipating Emerging Risks, Shifting Roles, and Regulatory Challenges.

This viewpoint develops the futures framework for clinical artificial intelligence governance (FF-CAIG), a conceptual and anticipatory framework for o...

A cloud-edge adaptive lightweight network with dynamic inference enables real-time ultrasound image segmentation.

Ultrasound image segmentation plays an important role in clinical diagnosis, but existing deep learning methods struggle to balance accuracy and effic...

Explainable and clinically audited hybrid self-supervised framework for multi-class DFU classification and mobile deployment.

Accurate and explainable classification of diabetic foot ulcers (DFUs) is vital for early intervention and patient management. This paper presents a C...

Development and external validation of an interpretable machine learning model for predicting prolonged postoperative ICU length of stay in coronary artery bypass grafting patients using MIMIC-IV 3.1 and eICU-CRD 2.0.

BACKGROUND: Prolonged postoperative intensive care unit (ICU) length of stay (LOS) after coronary artery bypass grafting (CABG) drives resource use ye...

Retinal vascular parameters as AI-driven biomarkers for pulse wave velocity assessment: a telemedicine strategy for cardiovascular risk assessment.

BACKGROUND: Pulse wave velocity (PWV), known as the gold standard for evaluating arterial stiffness, is limited by device dependence. This study aims ...

Metaheuristic-driven machine learning study for early detection and classification of Parkinson's disease using feature prioritization with pelican optimization algorithm.

Parkinson disease (PD) is a degenerative disorder of the brain and afflicts approximately 6 in 10 people aged 50 years or older. PD patients have moto...