Latest AI and machine learning research in military medicine for healthcare professionals.
Researchers and clinicians are increasingly looking to leverage artificial intelligence (AI) and digital tools to improve psychiatric care. Of particular promise is addressing the youth mental health crisis. Yet, the introduction of AI-enabled digital technologies for psychiatric treatment of young adults raises a host of ethical, legal, and societal issues (ELSI). To provide guidance in addressin...
Machine learning-based Intrusion Detection Systems (IDS) often report high detection accuracy under controlled, single-dataset evaluation, yet experience severe performance degradation when deployed in unseen network environments due to domain shift. To bridge this gap between laboratory benchmarking and real-world deployment, this paper presents TAN-IDS, a transfer-aware and deployment-oriented e...
BACKGROUND: Electroencephalography (EEG) interpretation for epilepsy diagnosis faces persistent challenges including specialist shortages, variable in...
BACKGROUND: Health care professionals' perceptions of telemedicine, its usability, and the presence of organizational barriers are important determina...
Unmanned aerial vehicles (UAVs) play a vital role in scenarios such as community safety patrol and disaster search-and-rescue operations due to their ...
BACKGROUND: Autism spectrum disorder (ASD) is often underdiagnosed in low- and middle-income countries due to limited specialist access, sociocultural...
Cancer therapy-related cardiac dysfunction remains a major cause of morbidity among cancer survivors and may interrupt life-saving oncologic therapy o...
Clinical artificial intelligence (AI) applications frequently fail to transition from short-term pilot projects into sustained components of routine c...
Background: Collaboration between nurse practitioners (NPs) and pharmacists is essential for comprehensive patient care, especially in telehealth sett...
BACKGROUND: Rare diseases affect more than 300 million people globally, and only about 5% have approved therapies. Lysosomal storage disorders (LSDs) ...
OBJECTIVE: Studies investigating resting-state functional connectivity of the amygdala and hippocampus have produced inconsistent findings. The author...
IMPORTANCE: Retinopathy of prematurity (ROP) screening requires frequent examinations to avoid missed treatment-requiring disease, but this approach i...
BACKGROUND: Artificial intelligence (AI) technologies continue to transform how we research human disease, diagnose and treat patients, and operate ho...
IMPORTANCE: Accurate prediction of intubation in critically ill patients could enable interventions that improve patient outcomes. However, the perfor...
DNA microarray is a transformative technique in genomics, enabling simultaneous examination of thousands of gene expression levels. However, noise, hi...
Objective. We developed stroke volume variation (SVV) Net, a deep learning-based model for estimating SVV, and validated its performance and clinical ...
PURPOSE: To evaluate the gradable rate of the retinal images acquired with DRSplus retinographer in patients with diabetes and to estimate the diabeti...
OBJECTIVES: Artificial Intelligence models are increasingly used in health care, yet global performance metrics can mask variations in reliability acr...
BACKGROUND: The integration of artificial intelligence into retinal practice represents more than a technological advancement; it constitutes an anthr...
BACKGROUND: Otitis media is common in children. Otoscopic differentiation of acute otitis media (AOM), otitis media with effusion (OME) and normal tym...