Practice Management

Staffing & Scheduling

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

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Showing 1681-1701 of 2,458 articles
GenAI and the psychology of work.

Work is a central source of identity and meaning. The rapid and widespread adoption of generative ar...

May 2025 40345947
Dynamic Network Flow Optimization for Task Scheduling in PTZ Camera Surveillance Systems

This paper presents a novel approach for optimizing the scheduling and control of Pan-Tilt-Zoom (P...

WDMamba: When Wavelet Degradation Prior Meets Vision Mamba for Image Dehazing

In this paper, we reveal a novel haze-specific wavelet degradation prior observed through wavelet ...

Technology prediction of a 3D model using Neural Network

Accurate estimation of production times is critical for effective manufacturing scheduling, yet tr...

TS-SNN: Temporal Shift Module for Spiking Neural Networks

Spiking Neural Networks (SNNs) are increasingly recognized for their biological plausibility and e...

Learning Unknown Spoof Prompts for Generalized Face Anti-Spoofing Using Only Real Face Images

Face anti-spoofing is a critical technology for ensuring the security of face recognition systems....

Integrating generative AI and machine learning classifiers for solving heterogenous MCGDM: a case of employee churn prediction.

Employee churn is a critical issue for companies and organizations, as it directly impacts productiv...

May 2025 40325106
Bayesian Federated Cause-of-Death Classification and Quantification Under Distribution Shift

In regions lacking medically certified causes of death, verbal autopsy (VA) is a critical and wide...

Privacy Preserving Machine Learning Model Personalization through Federated Personalized Learning

The widespread adoption of Artificial Intelligence (AI) has been driven by significant advances in...

Low-Precision Training of Large Language Models: Methods, Challenges, and Opportunities

Large language models (LLMs) have achieved impressive performance across various domains. However,...

A Comparative Study of Large Language Models and Human Personality Traits

Large Language Models (LLMs) have demonstrated human-like capabilities in language comprehension a...

Transition States Energies from Machine Learning: An Application to Reverse Water-Gas Shift on Single-Atom Alloys

Obtaining accurate transition state (TS) energies is a bottleneck in computational screening of co...

JointDiT: Enhancing RGB-Depth Joint Modeling with Diffusion Transformers

We present JointDiT, a diffusion transformer that models the joint distribution of RGB and depth. ...

Memory-Centric Computing: Solving Computing's Memory Problem

Computing has a huge memory problem. The memory system, consisting of multiple technologies at dif...

SacFL: Self-Adaptive Federated Continual Learning for Resource-Constrained End Devices

The proliferation of end devices has led to a distributed computing paradigm, wherein on-device ma...

LLMPrism: Black-box Performance Diagnosis for Production LLM Training Platforms

Large Language Models (LLMs) have brought about revolutionary changes in diverse fields, rendering...

Toward Practical Quantum Machine Learning: A Novel Hybrid Quantum LSTM for Fraud Detection

We present a novel hybrid quantum-classical neural network architecture for fraud detection that i...

Towards proactive self-adaptive AI for non-stationary environments with dataset shifts

Artificial Intelligence (AI) models deployed in production frequently face challenges in maintaini...

Who Gets the Callback? Generative AI and Gender Bias

Generative artificial intelligence (AI), particularly large language models (LLMs), is being rapid...

Subject Information Extraction for Novelty Detection with Domain Shifts

Unsupervised novelty detection (UND), aimed at identifying novel samples, is essential in fields l...

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