Staffing & Scheduling

Effects of Exoskeletal Lower Limb Robot Training on the Activities of Daily Living in Stroke Patients: Retrospective Pre-Post Comparison Using Propensity Score Matched Analysis.

PURPOSE: There is limited evidence of gait training using newly developed exoskeletal lower limb rob...

Memristor-based LSTM network with in situ training and its applications.

Artificial neural networks (ANNs), such as the convolutional neural network (CNN) and long short-ter...

Automatic segmentation of brain MRI using a novel patch-wise U-net deep architecture.

Accurate segmentation of brain magnetic resonance imaging (MRI) is an essential step in quantifying ...

AI-driven attenuation correction for brain PET/MRI: Clinical evaluation of a dementia cohort and importance of the training group size.

INTRODUCTION: Robust and reliable attenuation correction (AC) is a prerequisite for accurate quantif...

Robotic Surgical Training at Home: A Low-Fidelity Simulation Method.

OBJECTIVE: Laparoscopic box simulators provide surgical residents a cost-effective and accessible le...

DANTE: Deep alternations for training neural networks.

We present DANTE, a novel method for training neural networks using the alternating minimization pri...

Machine Learning for Brain Stroke: A Review.

Machine Learning (ML) delivers an accurate and quick prediction outcome and it has become a powerful...

A Deep Learning-Based Tumor Classifier Directly Using MS Raw Data.

Since the launch of Chinese Human Proteome Project (CNHPP) and Clinical Proteomic Tumor Analysis Con...

Robot applications for autism: a comprehensive review.

PURPOSE: Technological advances in robotics have brought about exciting developments in different ar...

Performance of machine learning classification models of autism using resting-state fMRI is contingent on sample heterogeneity.

Autism spectrum disorders (ASDs) are heterogeneous neurodevelopmental conditions. In fMRI studies, i...

Performance comparison of wavelet neural network and adaptive neuro-fuzzy inference system with small data sets.

In this work, performance of wavelet neural network (WNN) and adaptive neuro-fuzzy inference system ...

Detection of peripherally inserted central catheter (PICC) in chest X-ray images: A multi-task deep learning model.

BACKGROUND AND OBJECTIVE: Peripherally inserted central catheter (PICC) is a novel drug delivery mod...

A Review of Deep Learning for Screening, Diagnosis, and Detection of Glaucoma Progression.

UNLABELLED: Because of recent advances in computing technology and the availability of large dataset...

Reinventing radiation therapy with machine learning and imaging bio-markers (radiomics): State-of-the-art, challenges and perspectives.

Radiation therapy is a pivotal cancer treatment that has significantly progressed over the last deca...

Countermovement Jump Standards in Rugby League: What is a "Good" Performance?

McMahon, JJ, Lake, JP, Dos'Santos, T, Jones, PA, Thomasson, ML, and Comfort, P. Countermovement jump...

BCI training to move a virtual hand reduces phantom limb pain: A randomized crossover trial.

OBJECTIVE: To determine whether training with a brain-computer interface (BCI) to control an image o...

Artificial intelligence: a new frontier for anaesthesiology training.

Training a neural network for Gibbs and noise removal in diffusion MRI.

PURPOSE: To develop and evaluate a neural network-based method for Gibbs artifact and noise removal.

Robotics-assisted visual-motor training influences arm position sense in three-dimensional space.

BACKGROUND: Performing activities of daily living depends, among other factors, on awareness of the ...

Analysis of the pattern recognition algorithm of broadband satellite modulation signal under deformable convolutional neural networks.

This research aims to analyze the effects of different parameter estimation on the recognition perfo...

Delay-distribution-dependent state estimation for neural networks under stochastic communication protocol with uncertain transition probabilities.

In this paper, the protocol-based remote state estimation problem is considered for a kind of delaye...