Practice Management

Staffing & Scheduling

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

2,458 articles
Stay Ahead - Weekly Staffing & Scheduling research updates
Subscribe
Browse Categories
Showing 1744-1764 of 2,458 articles
AI Hiring with LLMs: A Context-Aware and Explainable Multi-Agent Framework for Resume Screening

Resume screening is a critical yet time-intensive process in talent acquisition, requiring recruit...

Timely Trajectory Reconstruction in Finite Buffer Remote Tracking Systems

Remote tracking systems play a critical role in applications such as IoT, monitoring, surveillance...

Open-Qwen2VL: Compute-Efficient Pre-Training of Fully-Open Multimodal LLMs on Academic Resources

The reproduction of state-of-the-art multimodal LLM pre-training faces barriers at every stage of ...

Generalization-aware Remote Sensing Change Detection via Domain-agnostic Learning

Change detection has essential significance for the region's development, in which pseudo-changes ...

The Role of Artificial Intelligence in Nursing Care: An Umbrella Review.

Artificial intelligence (AI) is revolutionizing nursing by enhancing decision-making, patient monito...

Apr 2025 40222025
Optimising Nurse-Patient Assignments: The Impact of Machine Learning Model on Care Dynamics-Discursive Paper.

BACKGROUND: Machine learning (ML) models can enhance patient-nurse assignments in healthcare organis...

Apr 2025 40269403
Optimizing Age of Information in Networks with Large and Small Updates

Modern sensing and monitoring applications typically consist of sources transmitting updates of di...

Quantum Generative Models for Image Generation: Insights from MNIST and MedMNIST

Quantum generative models offer a promising new direction in machine learning by leveraging quantu...

Embedding Shift Dissection on CLIP: Effects of Augmentations on VLM's Representation Learning

Understanding the representation shift on Vision Language Models like CLIP under different augment...

Optimizing Distributed Training Approaches for Scaling Neural Networks

This paper presents a comparative analysis of distributed training strategies for large-scale neur...

Niyama : Breaking the Silos of LLM Inference Serving

The widespread adoption of Large Language Models (LLMs) has enabled diverse applications with very...

An Efficient Training Algorithm for Models with Block-wise Sparsity

Large-scale machine learning (ML) models are increasingly being used in critical domains like educ...

How do language models learn facts? Dynamics, curricula and hallucinations

Large language models accumulate vast knowledge during pre-training, yet the dynamics governing th...

GLRD: Global-Local Collaborative Reason and Debate with PSL for 3D Open-Vocabulary Detection

The task of LiDAR-based 3D Open-Vocabulary Detection (3D OVD) requires the detector to learn to de...

UWarp: A Whole Slide Image Registration Pipeline to Characterize Scanner-Induced Local Domain Shift

Histopathology slide digitization introduces scanner-induced domain shift that can significantly i...

L4: Diagnosing Large-scale LLM Training Failures via Automated Log Analysis

As Large Language Models (LLMs) show their capabilities across various applications, training cust...

Empirical Analysis of the Impact of 5G Jitter on Time-Aware Shaper Scheduling in a 5G-TSN Network

Deterministic communications are essential for industrial automation, ensuring strict latency requ...

Adaptive Weighted Parameter Fusion with CLIP for Class-Incremental Learning

Class-incremental Learning (CIL) enables the model to incrementally absorb knowledge from new clas...

Out-of-distribution evaluations of channel agnostic masked autoencoders in fluorescence microscopy

Developing computer vision for high-content screening is challenging due to various sources of dis...

Revisiting Automatic Data Curation for Vision Foundation Models in Digital Pathology

Vision foundation models (FMs) are accelerating the development of digital pathology algorithms an...

Browse Categories