Latest AI and machine learning research in military medicine for healthcare professionals.
Recent advances in learning-based robot manipulation have produced policies with remarkable capabilities. Yet, reliability at deployment remains a fundamental barrier to real-world use, where distribution shift, compounding errors, and complex task dependencies collectively undermine system performance. This dissertation investigates how the reliability of learned robot policies can be improved at...
Recently, progress has been made on the Intra Pattern Copy (IPC) tool for JPEG XS, an image compression standard designed for low-latency and low-complexity coding. IPC performs wavelet-domain intra compensation predictions to reduce spatial redundancy in screen content. A key module of IPC is the displacement vector (DV) search, which aims to solve the optimal prediction reference offset. However...
Adverse drug events are a significant source of preventable harm, which has led to the development of automated pill recognition systems to enhance me...
Background Personalized medicine promises to tailor treatments to the individual, but it carries a hidden risk: mistaking statistical noise for action...
Background Clinicians in care management programs are often in low supply relative to patient demand, especially in US Medicaid programs, and must sim...
Scientific discovery pipelines typically involve complex, rigid, and time-consuming processes, from data preparation to analyzing and interpreting fin...
Clinical deployment of chest radiograph classifiers requires models that can be updated as new datasets become available without retraining on previou...
Pathology foundation models (PFMs) have enabled robust generalization in computational pathology through large-scale datasets and expansive architectu...
Transformer architectures have revolutionized machine learning across a wide range of domains, from natural language processing to scientific computin...
Importance: High-quality discharge summaries are essential for safe care transitions but contribute substantially to clinician documentation burden an...
Deploying learned control policies on humanoid robots is challenging: policies that appear robust in simulation can execute confidently in out-of-dist...
Modern natural language tools have potential to improve clinical workflows, but few have been successfully deployed in practice. Here, we present the ...
Accurate pose estimation underpins quantitative analysis of behavior, yet many deep learning-based tracking tools remain optimized for offline workflo...
Missed and delayed diagnosis remains a major challenge in rare disease care. At the initial clinical encounters, physicians assess rare disease risk u...
Chronic wounds affect over 1.2 million Canadians and incur healthcare costs exceeding $13 billion annually, with global expenditures approaching $149 ...
Abstract Purpose: Glaucoma, a leading cause of irreversible vision loss, often remains undiagnosed due to its asymptomatic progression and the limitat...
Image deblurring is a critical stage in mobile image signal processing pipelines, where the ability to restore fine structures and textures must be ba...
Sociotechnical challenges of machine learning in healthcare and social welfare are mismatches between how a machine learning tool functions and the st...
Deploying medical image segmentation models in routine clinical workflows is often constrained by on-premises infrastructure, where computational reso...
Recently, artificial intelligence (AI) has emerged as a transformative tool, enhancing the speed, accuracy, and scalability of bacterial diagnostics. ...