Practice Management

Staffing & Scheduling

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

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Showing 2206-2226 of 6,170 articles
Deflected Versus Preshaped Soft Pneumatic Actuators: A Design and Performance Analysis Toward Reliable Soft Robots.

Soft pneumatic actuators (SPAs) are customizable and conformable devices that enable desired motions...

Training data distribution significantly impacts the estimation of tissue microstructure with machine learning.

PURPOSE: Supervised machine learning (ML) provides a compelling alternative to traditional model fit...

Performance of deep convolutional neural network for classification and detection of oral potentially malignant disorders in photographic images.

Oral potentially malignant disorders (OPMDs) are a group of conditions that can transform into oral ...

Sports Training System Based on Convolutional Neural Networks and Data Mining.

In recent years, China's sports industry has achieved good development, but the efficiency of athlet...

Advances in bacterial concentration methods and their integration in portable detection platforms: A review.

Early detection and identification of microbial contaminants is crucial in many sectors, including c...

Application of Reinforcement Learning Algorithm Model in Gas Path Fault Intelligent Diagnosis of Gas Turbine.

Gas turbine is widely used because of its advantages of fast start and stop, no pollution, and high ...

Evaluating a new verbal working memory-balance program: a double-blind, randomized controlled trial study on Iranian children with dyslexia.

BACKGROUND: It is important to improve verbal Working Memory (WM) in reading disability, as it is a ...

Whole-slide imaging, tissue image analysis, and artificial intelligence in veterinary pathology: An updated introduction and review.

Since whole-slide imaging has been commercially available for over 2 decades, digital pathology has ...

The impact of training sample size on deep learning-based organ auto-segmentation for head-and-neck patients.

To investigate the impact of training sample size on the performance of deep learning-based organ au...

Performance improvement of weakly supervised fully convolutional networks by skip connections for brain structure segmentation.

PURPOSE: For the planning and navigation of neurosurgery, we have developed a fully convolutional ne...

A Few-Shot Learning-Based Siamese Capsule Network for Intrusion Detection with Imbalanced Training Data.

Network intrusion detection remains one of the major challenges in cybersecurity. In recent years, m...

Preoperative prediction of postoperative urinary retention in lumbar surgery: a comparison of regression to multilayer neural network.

OBJECTIVE: Postoperative urinary retention (POUR) is a common complication after spine surgery and i...

Hierarchical Pooling in Graph Neural Networks to Enhance Classification Performance in Large Datasets.

Deep learning methods predicated on convolutional neural networks and graph neural networks have ena...

Gait training with a wearable curara® robot for cerebellar ataxia: a single-arm study.

BACKGROUND: Ataxic gait is one of the most common and disabling symptoms in people with degenerative...

Neural network surgery: Combining training with topology optimization.

With ever increasing computational capacities, neural networks become more and more proficient at so...

Retention time prediction in hydrophilic interaction liquid chromatography with graph neural network and transfer learning.

The combination of retention time (RT), accurate mass and tandem mass spectra can improve the struct...

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