Latest AI and machine learning research in military medicine for healthcare professionals.
IMPORTANCE: Accurate prediction of intubation in critically ill patients could enable interventions that improve patient outcomes. However, the performance of intensive care physicians compared with machine learning (ML) models remains unknown. OBJECTIVES: To investigate intensive care physicians' ability to predict the need for intubation within 24 hours and compare their performance against an e...
DNA microarray is a transformative technique in genomics, enabling simultaneous examination of thousands of gene expression levels. However, noise, high dimensionality (typically 12,000-22,000 genes), small sample sizes (155-1097 samples) and class imbalance complicate the extraction of meaningful diagnostic patterns. This paper presents MICRO-AI (Microarray Classification and Recognition using Ar...
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...
Parkinson's disease (PD) affects 10Â million globally, with accurate staging essential for personalized treatment planning. Current UPDRS assessments a...
Large-scale combat operations (LSCOs) impose major constraints on battlefield medical systems, combining sustained casualty inflow, degraded communica...
OBJECTIVES: The objectives of this study are to map definitions of digital health, eHealth, mHealth, telehealth, telemedicine, and artificial intellig...
Posttraumatic stress disorder (PTSD) has been associated with structural brain alterations, suggesting accelerated brain aging. Evidence from peripher...
Artificial intelligence (AI) has rapidly expanded across gastroenterology, enabling advances in real-time endoscopic detection, radiologic interpretat...
As the use of artificial intelligence (AI) in healthcare becomes more pervasive, its application in the clinical care for those with Parkinson's disea...
Postoperative placement of patients into a regular ward, an intermediate-care unit (IMC), or an intensive care unit (ICU) is critical for balancing pa...
BACKGROUND: Medical ambient artificial intelligence (AI) scribes reduce documentation burden, but the current evidence is almost entirely from English...
Access to quality healthcare remains a persistent challenge in many low- and middle-income countries, especially for rural and underserved populations...
Electricity theft is one of the primary contributors of non-technical losses in contemporary power grids, and traditional centralized methods of detec...
Artificial intelligence (AI) has the potential to transform health care; however, successful integration of AI into health care requires overcoming ob...
BACKGROUND: The COVID-19 pandemic prompted rapid changes in medical education, accelerating the adoption of online and distance learning methods as al...
BACKGROUND: Approximately 3.8 billion people lack access to essential health services, and diagnostic interpretation remains a major bottleneck in rem...