Practice Management

Staffing & Scheduling

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

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A dual-channel language decoding from brain activity with progressive transfer training.

When we view a scene, the visual cortex extracts and processes visual information in the scene throu...

Robot-assisted gait training in individuals with spinal cord injury: A systematic review for the clinical effectiveness of Lokomat.

BACKGROUND: Spinal cord injury (SCI) is a critical medical condition that causes numerous impairment...

Deep learning for segmentation in radiation therapy planning: a review.

Segmentation of organs and structures, as either targets or organs-at-risk, has a significant influe...

Combining Sensors Information to Enhance Pneumatic Grippers Performance.

The gripper is the far end of a robotic arm. It is responsible for the contacts between the robot it...

The path to precision medicine for MS, from AI to patient recruitment: an interview with Mauricio Farez and Helen Onuorah.

This year’s World Brain Day is focused on stopping Multiple Sclerosis (MS). Although amazing progres...

Pre-Processing Method to Improve Cross-Domain Fault Diagnosis for Bearing.

Models trained with one system fail to identify other systems accurately because of domain shifts. T...

Analysis of Body Behavior Characteristics after Sports Training Based on Convolution Neural Network.

The use of artificial intelligence technology to analyze human behavior is one of the key research t...

Collaborative driving style classification method enabled by majority voting ensemble learning for enhancing classification performance.

The classification of driving styles plays a fundamental role in evaluating drivers' driving behavio...

Ensemble Prediction of Job Resources to Improve System Performance for Slurm-Based HPC Systems.

In this paper, we present a novel methodology for predicting job resources (memory and time) for sub...

Artificial Intelligence and COVID-19: A Systematic umbrella review and roads ahead.

Artificial Intelligence (AI) has played a substantial role in the response to the challenges posed b...

Robot-Assisted Gait Training in Patients with Multiple Sclerosis: A Randomized Controlled Crossover Trial.

Gait disorders represent one of the most disabling aspects in multiple sclerosis (MS) that strongly...

Advancing diagnostic performance and clinical usability of neural networks via adversarial training and dual batch normalization.

Unmasking the decision making process of machine learning models is essential for implementing diagn...

Fast deep neural correspondence for tracking and identifying neurons in using semi-synthetic training.

We present an automated method to track and identify neurons in , called 'fast Deep Neural Correspon...

Deep ConvNet: Non-Random Weight Initialization for Repeatable Determinism, Examined with FSGM.

A repeatable and deterministic non-random weight initialization method in convolutional layers of ne...

Health Recognition Algorithm for Sports Training Based on Bi-GRU Neural Networks.

The healthcare benefits associated with regular physical activity recognition and monitoring have be...

The application of artificial intelligence in hepatology: A systematic review.

The integration of human and artificial intelligence (AI) in medicine has only recently begun but it...

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