Military Medicine

Interrater Reliability of Electroencephalogram Interpretations in Febrile Comatose African Children: Implications for Automated Interpretation Algorithm Creation.

Electroencephalography (EEG) is a diagnostic and prognostic tool used worldwide in the clinical care of comatose patients. Scalability of EEG use in resource-limited settings is constrained by multiple factors, including the lack of neurophysiologist interpreters. Although machine learning offers a path to creation of automated interpretation algorithms, development is constrained by the need for ...

Telehealth Approaches for Pediatric Otitis Media and Clinical Outcomes: Scoping Review.

BACKGROUND: Otitis media (OM) is a common pediatric infection worldwide. Conventionally, accurate diagnosis depends on in-person pneumatic otoscopy, which is not always accessible, contributing to delayed care and inappropriate prescribing, especially in underserved settings. Rapid advances in telemedicine and digital tools have accelerated the development of remote approaches for assessing pediat...

Neutron-gamma discrimination based on STFT-DFF model and FPGA implementation.

In the field of neutron-gamma discrimination, traditional discrimination algorithms exhibit poor performance in the low-energy region, while machine l...

Patient perspectives about deployment of artificial intelligence decision support tools in a safety-net healthcare system.

OBJECTIVES: To assess patient awareness, trust, perceived benefits, and risks of artificial intelligence (AI) in clinical care within an urban safety-...

Artificial intelligence in surgical care within low-income and middle-income countries: a scoping review of development, validation, and deployment.

Artificial intelligence (AI) has the potential to expand access to high-quality surgical care in low-income and middle-income countries (LMICs), yet t...

Deployment of a machine learning-based predictive system for childhood diarrhea in Sub-Saharan Africa.

Diarrhea remains a leading cause of child mortality in Sub-Saharan Africa, necessitating advanced predictive tools for early intervention. Despite the...

[Expert consensus on the clinical application of robotic-assisted bronchoscopy].

Robotic-assisted bronchoscopy (RAB) is an emerging diagnostic and interventional technology which integrates thin-slice CT-based virtual airway recons...

Use of artificial intelligence for health science in low- and middle-income countries: NIH portfolio landscape, gaps and opportunities.

OBJECTIVES: To analyse the landscape of active US National Institutes of Health (NIH) artificial intelligence (AI) health research grants, with emphas...

Application of artificial intelligence in schizophrenia rehabilitation management: a systematic scoping review.

Artificial intelligence (AI) is increasingly used in mental health, yet its rehabilitation-oriented applications in schizophrenia have not been system...

Enhancing adverse drug event extraction and summarization for cancer drugs through large language models.

PURPOSE: Cancer treatments such as chemotherapy, targeted therapy, and immunotherapy can effectively combat malignant cells but frequently cause serio...

MS360°: a conceptual digital-first, data-driven hybrid care framework for personalised multiple sclerosis management.

This perspective introduces MS360°, a conceptual hybrid care model for the management of multiple sclerosis (MS). It integrates traditional on-site as...

Reimagining Thomas Lewis's perspective: using artificial intelligence tools to predict cardiovascular risk from computed tomography.

Artificial intelligence (AI) is reshaping cardiovascular imaging, transforming it from a set of diagnostic tests into powerful tools of precision medi...

Development, application and evaluation of an artificial intelligence (AI)-based platform (SurgSmart) for the automatic assessment of the critical view of safety (CVS) in laparoscopic cholecystectomy (LC).

BACKGROUND: Laparoscopic Cholecystectomy (LC) is the standard surgical treatment for symptomatic benign gallbladder diseases. Bile Duct Injury (BDI) i...

Artificial intelligence for automated detection of joint bleeding via ultrasound in hemophilia: advancing standardization.

BACKGROUND: Musculoskeletal ultrasound (US) is a noninvasive tool for joint assessment in persons with hemophilia. Early detection of joint bleeding u...

AI Triage in Primary Care: Building Safer and More Equitable Real-World Evidence.

Artificial intelligence triage in general practice is developing rapidly within the primary care digital transformation, promising efficiency gains an...

What's New: Sub-5-minute Knee Magnetic Resonance Imaging- Spectrum of Sports Injuries and Overuse Conditions.

Knee injuries are one of the most common complaints in sports medicine. Magnetic resonance imaging is an essential adjunct to clinical evaluation for ...

Patterns of AI Use in Clinical Work by Hospitalists: Survey Study.

BACKGROUND: Artificial intelligence (AI) tools are widely and freely available for clinical use. Understanding hospitalists' real-world adoption patte...

Attention-enhanced deep learning model for automated classification of hemorrhagic and ischemic stroke on CT imaging.

BACKGROUND: Stroke is a disease with extremely high mortality and disability rates worldwide. Hemorrhagic stroke and ischemic stroke require completel...

AI in Childbirth and Emerging Alternatives to Traditional Fertility Treatments.

Artificial Intelligence (AI) is revolutionizing reproductive medicine by enhancing fertility treatments, childbirth monitoring, and postnatal care. AI...

Agentic AI in Radiology: Evolution from Large Language Models to Future Clinical Integration.

The introduction of foundational models, specifically large language models, has promised a health care transformation. However, the field is rapidly ...