Practice Management

Staffing & Scheduling

Latest AI and machine learning research in staffing & scheduling for healthcare professionals.

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Showing 1492-1512 of 2,453 articles
Task-Agnostic Continual Learning for Chest Radiograph Classification

Clinical deployment of chest radiograph classifiers requires models that can be updated as new datas...

Distributional Deep Learning for Super-Resolution of 4D Flow MRI under Domain Shift

Super-resolution is widely used in medical imaging to enhance low-quality data, reducing scan time a...

Inject Where It Matters: Training-Free Spatially-Adaptive Identity Preservation for Text-to-Image Personalization

Personalized text-to-image generation aims to integrate specific identities into arbitrary contexts....

Towards reconstructing experimental sparse-view X-ray CT data with diffusion models

Diffusion-based image generators are promising priors for ill-posed inverse problems like sparse-vie...

Stimulus-Driven Thermodynamic Shifts and Geometric Reorganization in Mouse Primary Visual Cortex

Efficient coding is essential for sensory systems to extract meaningful information from the environ...

The scaffolding of individual variability in language processing by domain-general neural networks

Language processing is supported by distributed neural systems. Yet most research examines these sys...

Dissecting Subjectivity and the "Ground Truth" Illusion in Data Annotation

In machine learning, "ground truth" refers to the assumed correct labels used to train and evaluate ...

Ctrl&Shift: High-Quality Geometry-Aware Object Manipulation in Visual Generation

Object-level manipulation, relocating or reorienting objects in images or videos while preserving sc...

Neural Dynamics of Automatic Speech Production

Speech is a defining human behavior, and this ability depends critically on speech motor cortex. Whi...

Med-SegLens: Latent-Level Model Diffing for Interpretable Medical Image Segmentation

Modern segmentation models achieve strong predictive performance but remain largely opaque, limiting...

FastUSP: A Multi-Level Collaborative Acceleration Framework for Distributed Diffusion Model Inference

Large-scale diffusion models such as FLUX (12B parameters) and Stable Diffusion 3 (8B parameters) re...

FD-DB: Frequency-Decoupled Dual-Branch Network for Unpaired Synthetic-to-Real Domain Translation

Synthetic data provide low-cost, accurately annotated samples for geometry-sensitive vision tasks, b...

FD-DB: Frequency-Decoupled Dual-Branch Network for Unpaired Synthetic-to-Real Domain Translation

Synthetic data provide low-cost, accurately annotated samples for geometry-sensitive vision tasks, b...

Training Data Selection with Gradient Orthogonality for Efficient Domain Adaptation

Fine-tuning large language models (LLMs) for specialized domains often necessitates a trade-off betw...

Unseen Insights: An AI-Powered Exploration of Secure Patient Messages in Ophthalmology

Objective To characterize the clinical and administrative concerns communicated through secure ophth...

Representation Geometry as a Diagnostic for Out-of-Distribution Robustness

Robust generalization under distribution shift remains difficult to monitor and optimize in the abse...

Anomaly Detection via Mean Shift Density Enhancement

Unsupervised anomaly detection stands as an important problem in machine learning, with applications...

Robust Representation Learning in Masked Autoencoders

Masked Autoencoders (MAEs) achieve impressive performance in image classification tasks, yet the int...

From Pre- to Intra-operative MRI: Predicting Brain Shift in Temporal Lobe Resection for Epilepsy Surgery

Introduction: In neurosurgery, image-guided Neurosurgery Systems (IGNS) highly rely on preoperative ...

Your AI-Generated Image Detector Can Secretly Achieve SOTA Accuracy, If Calibrated

Despite being trained on balanced datasets, existing AI-generated image detectors often exhibit syst...

Trust Region Continual Learning as an Implicit Meta-Learner

Continual learning aims to acquire tasks sequentially without catastrophic forgetting, yet standard ...

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