Latest AI and machine learning research in military medicine for healthcare professionals.
Parkinson's disease (PD) affects 10 million globally, with accurate staging essential for personalized treatment planning. Current UPDRS assessments achieve < 93% accuracy due to subjective clinical judgment and unimodal data limitations, failing to capture complex genetic-neuroimaging-clinical interactions driving disease heterogeneity. This study introduces MAFNet, a novel deep learning framewor...
Large-scale combat operations (LSCOs) impose major constraints on battlefield medical systems, combining sustained casualty inflow, degraded communications, prolonged evacuation timelines, and limited opportunities for repeated clinical reassessment. Under such conditions, conventional triage frameworks-designed for episodic assessment and rapid evacuation-become insufficient. This narrative revie...
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...
The rapid growth of born-digital PDF documents has amplified the demand for fast, precise tabular data extraction on an industrial scale. State-of-the...
Postoperative placement of patients into a regular ward, an intermediate-care unit (IMC), or an intensive care unit (ICU) is critical for balancing pa...
BackgroundIndustrial weld defect detection is challenged by the minimal grayscale contrast between defects and the background, as well as by blurred d...
The development of perovskites and perovskite-inspired materials (PIMs) is driven by the need for efficient, non-toxic and stable solar energy convers...
BACKGROUND: Medical ambient artificial intelligence (AI) scribes reduce documentation burden, but the current evidence is almost entirely from English...
Brain-computer interfaces (BCIs) suffer from accuracy degradation as neural signals drift over time and vary across users, requiring frequent recalibr...
Despite advances in deep learning and transformer architectures, prior reviews have focused narrowly on traditional clinical decision support systems ...
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...
Electroencephalography (EEG) is a diagnostic and prognostic tool used worldwide in the clinical care of comatose patients. Scalability of EEG use in r...
BACKGROUND: Otitis media (OM) is a common pediatric infection worldwide. Conventionally, accurate diagnosis depends on in-person pneumatic otoscopy, w...
Encapsulation technology involves strategic methods that mask undesirables, preserve bioactive compounds, and control their delivery characteristics. ...