Staffing & Scheduling

Robot-Assisted Reaching Performance of Chronic Stroke and Healthy Individuals in a Virtual Versus a Physical Environment: A Pilot Study.

The aim of the current study was to examine the role of environment, whether virtual or physical, on...

Supervised Domain Adaptation for Automatic Sub-cortical Brain Structure Segmentation with Minimal User Interaction.

In recent years, some convolutional neural networks (CNNs) have been proposed to segment sub-cortica...

A Novel Memory-Scheduling Strategy for Large Convolutional Neural Network on Memory-Limited Devices.

Recently, machine learning, especially deep learning, has been a core algorithm to be widely used in...

Three ways to build a strong AI-training pipeline.

Spiking Neural Network Modelling Approach Reveals How Mindfulness Training Rewires the Brain.

There has been substantial interest in Mindfulness Training (MT) to understand how it can benefit he...

Differences in muscle activity and fatigue of the upper limb between Task-Specific training and robot assisted training among individuals post stroke.

OBJECTIVE: To compare the activity and fatigue of upper extremity muscles, pain levels, subject sati...

Heterogeneous effects of alveolar recruitment in acute respiratory distress syndrome: a machine learning reanalysis of the Alveolar Recruitment for Acute Respiratory Distress Syndrome Trial.

BACKGROUND: Despite a robust physiological rationale, recruitment manoeuvres with PEEP titration wer...

A simulation-based approach to improve decoded neurofeedback performance.

The neural correlates of specific brain functions such as visual orientation tuning and individual f...

Determining gradient conditions for peptide purification in RPLC with machine-learning-based retention time predictions.

A strategy for determining a suitable solvent gradient in silico in preparative peptide separations ...

Training Convolutional Neural Networks and Compressed Sensing End-to-End for Microscopy Cell Detection.

Automated cell detection and localization from microscopy images are significant tasks in biomedical...

Using machine learning to translate applicant work history into predictors of performance and turnover.

Work history information reflected in resumes and job application forms is commonly used to screen j...

A Technical Review of Convolutional Neural Network-Based Mammographic Breast Cancer Diagnosis.

This study reviews the technique of convolutional neural network (CNN) applied in a specific field o...

Robust segmentation of arterial walls in intravascular ultrasound images using Dual Path U-Net.

A Fully Convolutional Network (FCN) based deep architecture called Dual Path U-Net (DPU-Net) is prop...

Recent advances in physical reservoir computing: A review.

Reservoir computing is a computational framework suited for temporal/sequential data processing. It ...

Keeping it 100: Social Media and Self-Presentation in College Football Recruiting.

Social media provides a platform for individuals to craft personal brands and influence their percep...

Interpretable genotype-to-phenotype classifiers with performance guarantees.

Understanding the relationship between the genome of a cell and its phenotype is a central problem i...

Characterisation of nonlinear receptive fields of visual neurons by convolutional neural network.

A comprehensive understanding of the stimulus-response properties of individual neurons is necessary...

BD2K Training Coordinating Center's ERuDIte: the Educational Resource Discovery Index for Data Science.

Data science is a field that has developed to enable efficient integration and analysis of increasin...

Exploit fully automatic low-level segmented PET data for training high-level deep learning algorithms for the corresponding CT data.

We present an approach for fully automatic urinary bladder segmentation in CT images with artificial...

Robot-assisted gait training is not superior to intensive overground walking in multiple sclerosis with severe disability (the RAGTIME study): A randomized controlled trial.

BACKGROUND: Rehabilitation may attenuate the impact on mobility of patients with progressive multipl...

Deep learning for electroencephalogram (EEG) classification tasks: a review.

OBJECTIVE: Electroencephalography (EEG) analysis has been an important tool in neuroscience with app...