Latest AI and machine learning research in military medicine for healthcare professionals.
Background: The HERMES Kiosk (Healthcare Enhanced Recommendations through Artificial Intelligence & Expertise System) is designed to provide personalized Over-the-Counter (OTC) medication recommendations, addressing the limitations of traditional health kiosks. It integrates an advanced GAMENet model enhanced with Graph Attention Networks (GAT) and Multi-Head Cross-Attention (MHCA) while ensurin...
The increasing global prevalence of mental disorders, such as depression and PTSD, requires objective and scalable diagnostic tools. Traditional clinical assessments often face limitations in accessibility, objectivity, and consistency. This paper investigates the potential of multimodal machine learning to address these challenges, leveraging the complementary information available in text, aud...
The management of chronic heart failure presents significant challenges in modern healthcare, requiring continuous monitoring, early detection of ex...
Post-Traumatic Stress Disorder (PTSD) remains underdiagnosed in clinical settings, presenting opportunities for automated detection to identify pati...
Advances in wearable sensors and artificial intelligence have greatly enhanced the potential of digitised audio biomarkers for disease diagnostics and...
The development of artificial intelligence (AI) including generative large language models (LLMs) and software like ChatGPT is likely to significantly...
As AI technology advances, it is driving innovation across industries, increasing the demand for scalable AI project deployment. However, deployment...
Background Telemedicine has the potential to provide secure and cost-effective healthcare at the touch of a button. Nephrotic syndrome is a chronic ...
Large Vision-Language Models (LVLMs) are increasingly being explored for applications in telemedicine, yet their ability to engage with diverse pati...
Effective training and debriefing are critical in high-stakes, mission-critical environments such as disaster response, military simulations, and in...
We propose a novel dual-loop system that synergistically combines responsive neurostimulation (RNS) implants with artificial intelligence-driven wea...
The variability and biases in the real-world performance benchmarking of deep learning models for medical imaging compromise their trustworthiness f...
Patient mobility monitoring in intensive care is critical for ensuring timely interventions and improving clinical outcomes. While accelerometry-bas...
Medical image segmentation, particularly tumor segmentation, is a critical task in medical imaging, with U-Net being a widely adopted convolutional ...
Privacy-preserving medical decision support for kidney disease requires localized deployment of large language models (LLMs) while maintaining clini...
Recent advances have given rise to a spectrum of digital health technologies that have the potential to revolutionize the design and conduct of cardio...
Detection and classification of pulmonary nodules is a challenge in medical image analysis due to the variety of shapes and sizes of nodules and the...
In recent years, vision transformers (ViTs) have emerged as powerful and promising techniques for computer vision tasks such as image classification...
Professionals increasingly use Artificial Intelligence (AI) to enhance their capabilities and assist with task execution. While prior research has e...
The application of large language models (LLMs) in healthcare has the potential to revolutionize clinical decision-making, medical research, and pat...