Latest AI and machine learning research in military medicine for healthcare professionals.
Abstract Purpose: Glaucoma, a leading cause of irreversible vision loss, often remains undiagnosed d...
Image deblurring is a critical stage in mobile image signal processing pipelines, where the ability ...
Sociotechnical challenges of machine learning in healthcare and social welfare are mismatches betwee...
Deploying medical image segmentation models in routine clinical workflows is often constrained by on...
Recently, artificial intelligence (AI) has emerged as a transformative tool, enhancing the speed, ac...
Vision-Language Models (VLMs) offer promising capabilities for mobile devices, but their deploymen...
We investigate the feasibility of inferring emotional states exclusively from physiological signal...
Medical physics and clinical engineering (MPCE) professionals have a critical role in the safe and e...
In recent years, hip arthroscopy has made great progress and has been extended to the treatment of i...
The integration of artificial intelligence (AI) in medical imaging raises crucial ethical concerns...
A Wi-Fi-enabled device, or simply Wi-Fi device, sporadically broadcasts probe request frames (PRFs...
The performance of leaning-based perception algorithms suffer when deployed in out-of-distribution...
Imitation learning models for robotic tasks typically rely on multi-modal inputs, such as RGB imag...
Magnetic Resonance Fingerprinting (MRF) is a fast quantitative MR Imaging technique that provides ...
The emergence of new-generation artificial intelligence technology has brought numerous innovations ...
The integration of artificial intelligence (AI) and machine learning-enabled medical technologies in...
Prolonged Exposure (PE) therapy is an effective treatment for post-traumatic stress disorder (PTSD...
Safe deployment of machine learning (ML) models in safety-critical domains such as medical imaging...
Accurate and interpretable detection of depressive language in social media is useful for early in...
This position paper argues that post-deployment monitoring in clinical AI is underdeveloped and pr...
The distribution of data changes over time; models operating operating in dynamic environments nee...