Staffing & Scheduling

Swarm intelligence-based packet scheduling for future intelligent networks.

Network operations involve several decision-making tasks. Some of these tasks are related to operato...

Evaluation of deep learning training strategies for the classification of bone marrow cell images.

BACKGROUND AND OBJECTIVE: The classification of bone marrow (BM) cells by light microscopy is an imp...

Artificial Intelligence to Speed Up Training in Echocardiography: The Next Frontier.

Sample size and predictive performance of machine learning methods with survival data: A simulation study.

Prediction models are increasingly developed and used in diagnostic and prognostic studies, where th...

Miner Fatigue Detection from Electroencephalogram-Based Relative Power Spectral Topography Using Convolutional Neural Network.

Fatigue of miners is caused by intensive workloads, long working hours, and shift-work schedules. It...

Improving the classification of veterinary thoracic radiographs through inter-species and inter-pathology self-supervised pre-training of deep learning models.

The analysis of veterinary radiographic imaging data is an essential step in the diagnosis of many t...

Gait training using a wearable robotic hip device for incomplete spinal cord injury: A preliminary study.

CONTEXT/OBJECTIVE: To explore changes in gait functions for patients with chronic spinal cord injury...

Self-supervised multi-modal training from uncurated images and reports enables monitoring AI in radiology.

The escalating demand for artificial intelligence (AI) systems that can monitor and supervise human ...

Effects of high-intensity gait training with and without soft robotic exosuits in people post-stroke: a development-of-concept pilot crossover trial.

INTRODUCTION: High-intensity gait training is widely recognized as an effective rehabilitation appro...

A Deep Learning Approach for Automatic and Objective Grading of the Motor Impairment Severity in Parkinson's Disease for Use in Tele-Assessments.

Wearable sensors provide a tool for at-home monitoring of motor impairment progression in neurologic...

Individualized Stress Mobile Sensing Using Self-Supervised Pre-Training.

Stress is widely recognized as a major contributor to a variety of health issues. Stress prediction ...

How intra-source imbalanced datasets impact the performance of deep learning for COVID-19 diagnosis using chest X-ray images.

Over the past decade, the use of deep learning has been widely increasing in the medical image diagn...

Towards a Better Performance in Facial Expression Recognition: A Data-Centric Approach.

Facial expression is the best evidence of our emotions. Its automatic detection and recognition are ...

ConTraNet: A hybrid network for improving the classification of EEG and EMG signals with limited training data.

OBJECTIVE: Bio-Signals such as electroencephalography (EEG) and electromyography (EMG) are widely us...

Characterizing the Stability of Angiotensin II in 0.9% Sodium Chloride Using High Performance Liquid Chromatography and Liquid Chromatography Tandem Mass Spectrometry.

The purpose of this study was to evaluate the stability of angiotensin II in 0.9% sodium chloride f...

AdaSAM: Boosting sharpness-aware minimization with adaptive learning rate and momentum for training deep neural networks.

Sharpness aware minimization (SAM) optimizer has been extensively explored as it can generalize bett...

Configurations of human-centered AI at work: seven actor-structure engagements in organizations.

PURPOSE: The discourse on the human-centricity of AI at work needs contextualization. The aim of thi...

Adaptive bias-variance trade-off in advantage estimator for actor-critic algorithms.

Actor-critic methods are leading in many challenging continuous control tasks. Advantage estimators,...

Event-triggered impulsive quasi-synchronization for BAM neural networks with reliable redundant channel.

This work addresses the quasi-synchronization of delay master-slave BAM neural networks. To improve ...

Learning Skill Training Schedules From Domain Experts for a Multi-Patient Multi-Robot Rehabilitation Gym.

A robotic gym with multiple rehabilitation robots allows multiple patients to exercise simultaneousl...

Application possibilities of artificial intelligence in facial vascularized composite allotransplantation-a narrative review.

Facial vascularized composite allotransplantation (FVCA) is an emerging field of reconstructive surg...