Practice Management

Staffing & Scheduling

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

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Showing 484-504 of 6,123 articles
Perceptions and Attitudes of Registered Nurses and Nursing Students Toward Advanced Technology and Artificial Intelligence: A Review of Literature.

The use of technology in healthcare and healthcare education settings has increased rapidly across t...

An quality evaluation method based on three-dimensional integration and machine learning: Advanced data processing.

This study presents an innovative approach for the quality evaluation of traditional Chinese medicin...

Integrating convolutional layers and biformer network with forward-forward and backpropagation training.

Accurate molecular property prediction is crucial for drug discovery and computational chemistry, fa...

Machine Learning in Small-Molecule Mass Spectrometry.

Tandem mass spectrometry (MS/MS) is crucial for small-molecule analysis; however, traditional comput...

Review of 2024 publications on the applications of artificial intelligence in rheumatology.

The integration of artificial intelligence (AI) into rheumatology has revolutionized research and cl...

Deeply supervised two stage generative adversarial network for stain normalization.

The color variations present in histopathological images pose a significant challenge to computation...

Investigation of Inter-Patient, Intra-Patient, and Patient-Specific Based Training in Deep Learning for Classification of Heartbeat Arrhythmia.

Effective diagnosis of electrocardiogram (ECG) is one of the simplest and fastest ways to assess the...

Is it necessary? A framework for assessing the utility of A.I. in HRM practices.

Artificial Intelligence is expected to be a value-adding intervention in HRM processes; however, the...

Artificial Intelligence Algorithms, Bias, and Innovation: Implications for Social Work.

PURPOSE: Artificial Intelligence (AI) technologies are rapidly expanding across diverse contexts. As...

Integration of Virtual Technology and Artificial Intelligence Improves Satisfaction, Patient Safety, and Nursing Workforce Efficiency.

BACKGROUND: Virtual care technology including artificial intelligence (AI) may augment nursing funct...

Exploring temporal information dynamics in Spiking Neural Networks: Fast Temporal Efficient Training.

BACKGROUND: Spiking Neural Networks (SNNs) hold significant potential in brain simulation and tempor...

Of Pilots and Copilots: The Evolving Role of Artificial Intelligence in Clinical Neurophysiology.

Artificial intelligence (AI) is revolutionizing clinical neurophysiology (CNP), particularly in its ...

Deep learning methods for clinical workflow phase-based prediction of procedure duration: a benchmark study.

This study evaluates the performance of deep learning models in the prediction of the end time of pr...

Artificial Intelligence in Peer Review: Enhancing Efficiency While Preserving Integrity.

The rapid advancement of artificial intelligence (AI) has transformed various aspects of scientific ...

Label as Equilibrium: A performance booster for Graph Neural Networks on node classification.

Graph Neural Network (GNN) is effective in graph mining and has become a dominant solution to the no...

ADFQ-ViT: Activation-Distribution-Friendly post-training Quantization for Vision Transformers.

Vision Transformers (ViTs) have exhibited exceptional performance across diverse computer vision tas...

Integrated learning framework for enhanced specific surface area, pore size, and pore volume prediction of biochar.

Specific surface area, pore size, and pore volume are essential biochar properties. Optimization typ...

Unsupervised learning from EEG data for epilepsy: A systematic literature review.

BACKGROUND AND OBJECTIVES: Epilepsy is a neurological disorder characterized by recurrent epileptic ...

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