Latest AI and machine learning research in military medicine for healthcare professionals.
PURPOSE: Foundation models pretrained on structured electronic health record (EHR) data promise improved predictive performance, sample efficiency and resilience to distribution shifts. However, model design, scale and use remain unclear. Objectives were to characterize foundation models pretrained on structured EHR data; examine temporal trends in model application and scale, architecture and des...
The development of deep learning models for 3D knee MRI analysis is critically constrained by the scarcity of large, annotated datasets. Few-shot learning (FSL) offers a promising pathway to leverage small data, but its effective application to volumetric medical imaging remains underexplored. This study introduces MedNet-FS, a 3D FSL framework that strategically integrates domain-specific pre-tra...
BACKGROUND: Despite the increasing number of studies on prediction models for identifying the risk of postpartum post-traumatic stress disorder (PP-PT...
Artificial intelligence is expanding rapidly in cardiovascular medicine, but its value in internal medicine depends less on raw model performance than...
BACKGROUND: Alzheimer disease (AD) is a progressive neurodegenerative disorder with rapidly growing global prevalence. Early detection is critical for...
Effective autonomous monitoring of marine litter is vital to reduce marine pollution and protect marine ecosystems. However, current underwater detect...
Online artificial intelligence (AI) algorithms are an important component of digital health interventions. These online algorithms are designed to con...
Surface-enhanced Raman spectroscopy (SERS) is being transformed by the widespread adoption of artificial intelligence across the full methodological s...
PURPOSE: For patients with oral cavity cancer (OCC) and oropharyngeal cancer (OPC), the time between initial diagnosis and start of treatment can have...
The article presents a real-time mango leaf disease detection framework with embedded edge deployment, using UAV-based multispectral imaging combined ...
Developing sustainable bioelectronics that simultaneously integrate mechanical robustness, high conductivity, biocompatibility, and system-level funct...
Artificial intelligence (AI) has progressed from technical research to routine clinical use, reaching an inflection point where technological capabili...
BACKGROUND: Health care workers (HCWs) face sustained psychological demands that place them at heightened risk for burnout and posttraumatic stress di...
Artificial intelligence (AI) as a medical device is now progressively entering routine ophthalmic care, yet its impact is still mostly evaluated in te...
The accurate identification of foraging locations is critical for wildlife conservation. While remote sensing and biologging devices provide much of t...
Modern software development relies on automated build systems that compile and test code whenever developers make changes. Predicting whether these bu...
Background: A conversation between a victim and a perpetrator of sexual abuse has the potential to reduce posttraumatic stress disorder (PTSD) symptom...
BACKGROUND: Real-time warning and prevention of sports injuries are core challenges in the fields of sports medicine and health management. Traditiona...
OBJECTIVES: Large language models (LLMs) are increasingly explored as decision-support tools in medical imaging. However, their ability to align with ...
Research on artificial intelligence (AI) and mental health has focused largely on harms at deployment, including chatbot safety, sycophancy, and AI-as...