Work Force

A New Design Scheme for Intelligent Upper Limb Rehabilitation Training Robot.

In view of the urgent need for intelligent rehabilitation equipment for some disabled people, an int...

Towards large-scale case-finding: training and validation of residual networks for detection of chronic obstructive pulmonary disease using low-dose CT.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is underdiagnosed in the community. Thoraci...

Key components of mechanical work predict outcomes in robotic stroke therapy.

BACKGROUND: Clinical practice typically emphasizes active involvement during therapy. However, tradi...

Exploring the Role of Artificial Intelligence in an Emergency and Trauma Radiology Department.

Emergency and trauma radiologists, emergency department's physicians and nurses, researchers, depart...

Training of deep neural networks for the generation of dynamic movement primitives.

Dynamic movement primitives (DMPs) have proven to be an effective movement representation for motor ...

Training instance segmentation neural network with synthetic datasets for crop seed phenotyping.

In order to train the neural network for plant phenotyping, a sufficient amount of training data mus...

Machine learning modelling of neuropsychological performance could determine vocational training outcome after a brain injury: Case report.

Effectively training neural networks for stock index prediction: Predicting the S&P 500 index without using its index data.

We propose a novel method for training neural networks to predict the future prices of stock indexes...

Automatic diagnosis of the 12-lead ECG using a deep neural network.

The role of automatic electrocardiogram (ECG) analysis in clinical practice is limited by the accura...

Quantitative Assessment of Motor Function for Patients with a Stroke by an End-Effector Upper Limb Rehabilitation Robot.

With the popularization of rehabilitation robots, it is necessary to develop quantitative motor func...

Topics and trends in artificial intelligence assisted human brain research.

Artificial intelligence (AI) assisted human brain research is a dynamic interdisciplinary field with...

Improving patient outcomes with regenerative medicine: How the Regenerative Medicine Manufacturing Society plans to move the needle forward in cell manufacturing, standards, 3D bioprinting, artificial intelligence-enabled automation, education, and training.

The Regenerative Medicine Manufacturing Society (RMMS) is the first and only professional society de...

Effects of robotic gait training after stroke: A meta-analysis.

BACKGROUND: Robotic devices are often used in rehabilitation and might be efficient to improve walki...

Chronic gastritis classification using gastric X-ray images with a semi-supervised learning method based on tri-training.

High-quality annotations for medical images are always costly and scarce. Many applications of deep ...

Multi-way backpropagation for training compact deep neural networks.

Depth is one of the key factors behind the success of convolutional neural networks (CNNs). Since Re...

New optimization algorithms for neural network training using operator splitting techniques.

In the following paper we present a new type of optimization algorithms adapted for neural network t...

Robotic Cholecystectomy Is a Safe Educational Alternative to Laparoscopic Cholecystectomy During General Surgical Training: A Pilot Study.

OBJECTIVE: The role of robotic surgery in general surgery (GS) continues to expand. Several programs...

Effects of Robot-Assisted Gait Training in Individuals with Spinal Cord Injury: A Meta-analysis.

BACKGROUND: To investigate the effects of robot-assisted gait training (RAGT) on spasticity and pain...

Improving the binding affinity estimations of protein-ligand complexes using machine-learning facilitated force field method.

Scoring functions are routinely deployed in structure-based drug design to quantify the potential fo...

Modeling the Research Landscapes of Artificial Intelligence Applications in Diabetes (GAP).

The rising prevalence and global burden of diabetes fortify the need for more comprehensive and effe...

Breaking Down Structural Diversity for Comprehensive Prediction of Ion-Neutral Collision Cross Sections.

Identification of unknowns is a bottleneck for large-scale untargeted analyses like metabolomics or ...