Latest AI and machine learning research in staffing & scheduling for healthcare professionals.
Background: Previous machine learning models to intraoperatively predict the molecular status of gli...
The Post-baccalaureate Research Education Program (PREP), established by the National Institute of G...
The accurate recovery of constituent-level optical properties from integrating sphere measurements i...
The inherent electronic and speckle noise complicates clinical interpretation of ultrasound images. ...
Differentiable vector graphics have enabled powerful gradient-based optimization of vector primitive...
Diffusion models (DMs) have demonstrated remarkable success in real-world image super-resolution (SR...
Deep learning-based facial phenotyping represents a major paradigm shift in the diagnosis of rare an...
ABSTRACT Background The clinical assessment of knee stability after an Anterior Cruciate Ligament (A...
We present You Only Stack Once (YOSO), an automated pipeline designed to detect faint, slow-moving S...
Power-of-two (PoT) quantization significantly reduces the size of deep neural networks (DNNs) and re...
Continual learning (CL) is essential for deploying medical image segmentation models in clinical env...
Reinforcement learning fine-tuning has become the dominant approach for aligning diffusion models wi...
Cross-scene hyperspectral image (HSI) classification stands as a fundamental research topic in remot...
While linear-complexity attention mechanisms offer a promising alternative to Softmax attention for ...
Continuous monitoring of bipolar disorder agitation via voice biomarkers requires disentangling stab...
Federated learning (FL) holds great potential for medical applications. However, statistical heterog...
Single-cell foundation models (scFMs) have shown promise as transferable representations of cellular...
Artificial Intelligence (AI) is transforming therapeutic discovery by scoring a large set of promisi...
Domain shift, where deviations between training and deployment data distributions degrade model perf...
Face swapping aims to optimize realistic facial image generation by leveraging the identity of a sou...
Convolutional neural networks (CNNs) remain a central approach in image classification, but their pe...