Work Force

Deep Adversarial Training for Multi-Organ Nuclei Segmentation in Histopathology Images.

Nuclei mymargin segmentation is a fundamental task for various computational pathology applications ...

Simulator-generated training datasets as an alternative to using patient data for machine learning: An example in myocardial segmentation with MRI.

BACKGROUND AND OBJECTIVE: Supervised Machine Learning techniques have shown significant potential in...

Robot-Assisted Arm Training versus Therapist-Mediated Training after Stroke: A Systematic Review and Meta-Analysis.

BACKGROUND: More than two-thirds of stroke patients have arm motor impairments and function deficits...

Deep neural network for water/fat separation: Supervised training, unsupervised training, and no training.

PURPOSE: To use a deep neural network (DNN) for solving the optimization problem of water/fat separa...

Influence of Optimization Design Based on Artificial Intelligence and Internet of Things on the Electrocardiogram Monitoring System.

With the increasing emphasis on remote electrocardiogram (ECG) monitoring, a variety of wearable rem...

Electromechanical-assisted training for walking after stroke.

BACKGROUND: Electromechanical- and robot-assisted gait-training devices are used in rehabilitation a...

A Novel Use of Artificial Intelligence to Examine Diversity and Hospital Performance.

BACKGROUND: The US population is becoming more racially and ethnically diverse. Research suggests th...

Development, evaluation, and validation of machine learning models for COVID-19 detection based on routine blood tests.

OBJECTIVES: The rRT-PCR test, the current gold standard for the detection of coronavirus disease (CO...

Robot-assisted Gait Training Using Welwalk in Hemiparetic Stroke Patients: An Effectiveness Study with Matched Control.

OBJECTIVE: Although studies on the efficacy of the rehabilitation robot are increasing, there are fe...

Understanding the geometric diversity of inorganic and hybrid frameworks through structural coarse-graining.

Much of our understanding of complex structures is based on simplification: for example, metal-organ...

Wearable Biofeedback Improves Human-Robot Compliance during Ankle-Foot Exoskeleton-Assisted Gait Training: A Pre-Post Controlled Study in Healthy Participants.

The adjunctive use of biofeedback systems with exoskeletons may accelerate post-stroke gait rehabili...

Effects of walking distance over robot-assisted training on walking ability in chronic stroke patients.

An understanding of the dose-response during training is important to identify the rehabilitation pr...

Deep learning for automated analysis of fish abundance: the benefits of training across multiple habitats.

Environmental monitoring guides conservation and is particularly important for aquatic habitats whic...

Activity-based training with the Myosuit: a safety and feasibility study across diverse gait disorders.

BACKGROUND: Physical activity is a recommended part of treatment for numerous neurological and neuro...

Improving CNN training on endoscopic image data by extracting additionally training data from endoscopic videos.

In this work we present a technique to deal with one of the biggest problems for the application of ...

[Ethical, legal and social requirements for assistive robots in healthcare : Viewpoint of management personnel in hospitals and nursing homes].

BACKGROUND: In 2030 there will be 4 million people in need of care in Germany; however, the nursing ...

Characterization and wearability evaluation of a fully portable wrist exoskeleton for unsupervised training after stroke.

BACKGROUND: Chronic hand and wrist impairment are frequently present following stroke and severely l...

Pathology training in the age of artificial intelligence.

Using machine learning of clinical data to diagnose COVID-19: a systematic review and meta-analysis.

BACKGROUND: The recent Coronavirus Disease 2019 (COVID-19) pandemic has placed severe stress on heal...

Federated Gradient Averaging for Multi-Site Training with Momentum-Based Optimizers.

Multi-site training methods for artificial neural networks are of particular interest to the medical...

Sensor-based indicators of performance changes between sessions during robotic surgery training.

Training of surgeons is essential for safe and effective use of robotic surgery, yet current assessm...