Staffing & Scheduling

Distinct subtypes of inhibitory interneurons differentially promote the propagation of rate and temporal codes in the feedforward neural network.

Sensory information is believed to be encoded in neuronal spikes using two different neural codes, t...

Artificial Intelligence Pertaining to Cardiothoracic Imaging and Patient Care: Beyond Image Interpretation.

Artificial intelligence (AI) is a broad field of computational science that includes many subsets. T...

Polar labeling: silver standard algorithm for training disease classifiers.

MOTIVATION: Expert-labeled data are essential to train phenotyping algorithms for cohort identificat...

[A fusion network model based on limited training samples for the automatic segmentation of pelvic endangered organs].

When applying deep learning to the automatic segmentation of organs at risk in medical images, we co...

Machine Learning and Medical Appointment Scheduling: Creating and Perpetuating Inequalities in Access to Health Care.

From development to deployment: dataset shift, causality, and shift-stable models in health AI.

Role of Instruction Adherence During Highly Structured Robotic Arm Training on Motor Outcomes for Individuals After Chronic Stroke.

The aim of this study was to examine the effects of instruction adherence on upper limb motor outcom...

Performance of a Deep Neural Network Algorithm Based on a Small Medical Image Dataset: Incremental Impact of 3D-to-2D Reformation Combined with Novel Data Augmentation, Photometric Conversion, or Transfer Learning.

Collecting and curating large medical-image datasets for deep neural network (DNN) algorithm develop...

Pre-trained language model augmented adversarial training network for Chinese clinical event detection.

Clinical event detection (CED) is a hot topic and essential task in medical artificial intelligence,...

A TrAdaBoost Method for Detecting Multiple Subjects' N200 and P300 Potentials Based on Cross-Validation and an Adaptive Threshold.

Traditional training methods need to collect a large amount of data for every subject to train a sub...

[A review on multi-modal human motion representation recognition and its application in orthopedic rehabilitation training].

Human motion recognition (HAR) is the technological base of intelligent medical treatment, sports tr...

Performance of a Deep Learning Algorithm for Automated Segmentation and Quantification of Traumatic Pelvic Hematomas on CT.

The volume of pelvic hematoma at CT has been shown to be the strongest independent predictor of majo...

The reactome pathway knowledgebase.

The Reactome Knowledgebase (https://reactome.org) provides molecular details of signal transduction,...

Putting the world back to work: An expert system using big data and artificial intelligence in combating the spread of COVID-19 and similar contagious diseases.

BACKGROUND: To combat COVID-19, curb the pandemic, and manage containment, governments around the wo...

Effect of robot-assisted gait training on motor functions in adolescent and young adult patients with bilateral spastic cerebral palsy: A randomized controlled trial.

BACKGROUND: Robot-assisted gait training (RAGT) allows an intensive gait training in patients with c...

Artificial Intelligence Forecasting Census and Supporting Early Decisions.

Matching resources to demand is a daily challenge for hospital leadership. In interdisciplinary coll...

Impact of smart force feedback rehabilitation robot training on upper limb motor function in the subacute stage of stroke.

OBJECTIVE: To explore the impact of rehabilitation robot training (RRT) on upper limb motor function...

Effects of innovative hip-knee-ankle interlimb coordinated robot training on ambulation, cardiopulmonary function, depression, and fall confidence in acute hemiplegia.

BACKGROUND: While Walkbot-assisted locomotor training (WLT) provided ample evidence on balance and g...

Robot-assisted gait training promotes brain reorganization after stroke: A randomized controlled pilot study.

BACKGROUND: Robot-assisted gait training (RAGT) can improve walking ability after stroke but the und...

Lessons learned from conducting a pragmatic, randomized, crossover trial on robot-assisted gait training in children with cerebral palsy (PeLoGAIT).

PURPOSE: To investigate the effectiveness of outpatient robot-assisted gait training (RAGT) in ambul...

Effects of robot-assisted gait training alongside conventional therapy on the development of walking in children with cerebral palsy.

PURPOSE: To investigate the effects of robot-assisted gait training (RAGT) alongside conventional th...