Latest AI and machine learning research in military medicine for healthcare professionals.
Vision-Language Models (VLMs) offer promising capabilities for mobile devices, but their deployment faces significant challenges due to computational limitations and energy inefficiency, especially for real-time applications. This study provides a comprehensive survey of deployment frameworks for VLMs on mobile devices, evaluating llama.cpp, MLC-Imp, and mllm in the context of running LLaVA-1.5 ...
We investigate the feasibility of inferring emotional states exclusively from physiological signals, thereby presenting a privacy-preserving alternative to conventional facial recognition techniques. We conduct a performance comparison of classical machine learning algorithms and hybrid quantum machine learning (QML) methods with a quantum kernel-based model. Our results indicate that the quantu...
Medical physics and clinical engineering (MPCE) professionals have a critical role in the safe and effective deployment of artificial intelligence (AI...
In recent years, hip arthroscopy has made great progress and has been extended to the treatment of intra-articular or periarticular diseases. However,...
The integration of artificial intelligence (AI) in medical imaging raises crucial ethical concerns at every stage of its development, from data coll...
A Wi-Fi-enabled device, or simply Wi-Fi device, sporadically broadcasts probe request frames (PRFs) to discover nearby access points (APs), whether ...
The performance of leaning-based perception algorithms suffer when deployed in out-of-distribution and underrepresented environments. Outdoor robots...
Imitation learning models for robotic tasks typically rely on multi-modal inputs, such as RGB images, language, and proprioceptive states. While pro...
Magnetic Resonance Fingerprinting (MRF) is a fast quantitative MR Imaging technique that provides multi-parametric maps with a single acquisition. N...
The emergence of new-generation artificial intelligence technology has brought numerous innovations to the healthcare field, including telemedicine an...
The integration of artificial intelligence (AI) and machine learning-enabled medical technologies into clinical practice is expanding at an unpreceden...
Prolonged Exposure (PE) therapy is an effective treatment for post-traumatic stress disorder (PTSD), but evaluating therapist fidelity remains labor...
Safe deployment of machine learning (ML) models in safety-critical domains such as medical imaging requires detecting inputs with characteristics no...
Accurate and interpretable detection of depressive language in social media is useful for early interventions of mental health conditions, and has i...
This position paper argues that post-deployment monitoring in clinical AI is underdeveloped and proposes statistically valid and label-efficient tes...
The distribution of data changes over time; models operating operating in dynamic environments need retraining. But knowing when to retrain, without...
Complete blood cell detection holds significant value in clinical diagnostics. Conventional manual microscopy methods suffer from time inefficiency ...
Skin cancer is among the most prevalent and life-threatening diseases worldwide, with early detection being critical to patient outcomes. This work ...
Integrating Traditional Chinese Medicine (TCM) and Modern Medicine faces significant barriers, including the absence of unified frameworks and standar...
Similar to major natural disasters and large-scale wars, the events of October 7th and the retaliatory Iron Swords war resulted in both direct and ind...