Work Force

Artificial intelligence in surgical education and training: opportunities, challenges, and ethical considerations - correspondence.

Gait training with a wearable powered robot during stroke rehabilitation: a randomized parallel-group trial.

BACKGROUND: We have developed a wearable rehabilitation robot, "curara®," and examined its immediate...

Public sentiment analysis on urban regeneration: A massive data study based on sentiment knowledge enhanced pre-training and latent Dirichlet allocation.

BACKGROUND: Public satisfaction is the ultimate goal and an important determinant of China's urban r...

A Data-Efficient Deep Learning Strategy for Tissue Characterization via Quantitative Ultrasound: Zone Training.

Deep learning (DL) powered biomedical ultrasound imaging is an emerging research field where researc...

Performance-Based Robotic Training in Individuals with Subacute Stroke: Differences between Responders and Non-Responders.

The high variability of upper limb motor recovery with robotic training (RT) in subacute stroke unde...

A systematic review of video-based educational interventions in robotic surgical training.

As robotic surgical procedures become more prevalent in practice, there is a demand for effective an...

A multi-view co-training network for semi-supervised medical image-based prognostic prediction.

Prognostic prediction has long been a hotspot in disease analysis and management, and the developmen...

Towards a robust and compact deep learning system for primary detection of early Barrett's neoplasia: Initial image-based results of training on a multi-center retrospectively collected data set.

INTRODUCTION: Endoscopic detection of early neoplasia in Barrett's esophagus is difficult. Computer ...

How to apply evidence-based practice to the use of artificial intelligence in radiology (EBRAI) using the data algorithm training output (DATO) method.

OBJECTIVE: As the number of radiology artificial intelligence (AI) papers increases, there are new c...

A Preliminary Study of Deep Learning Sensor Fusion for Pedestrian Detection.

Most pedestrian detection methods focus on bounding boxes based on fusing RGB with lidar. These meth...

Effect of Robot-Assisted Gait Training on Multiple Sclerosis: A Systematic Review and Meta-analysis of Randomized Controlled Trials.

BACKGROUND: In recent meta-analyses, robot-assisted gait training for patients with multiple scleros...

Artificial intelligence assisted telehealth for nursing: A scoping review.

BACKGROUND: Due to the COVID-19 pandemic, telehealth resurfaced as a convenient efficient healthcare...

Reproducibility of a combined artificial intelligence and optimal-surface graph-cut method to automate bronchial parameter extraction.

OBJECTIVES: Computed tomography (CT)-based bronchial parameters correlate with disease status. Segme...

Daily reference evapotranspiration prediction for irrigation scheduling decisions based on the hybrid PSO-LSTM model.

The shortage of available water resources and climate change are major factors affecting agricultura...

Fuzzy Adaptive Passive Control Strategy Design for Upper-Limb End-Effector Rehabilitation Robot.

Robot-assisted rehabilitation therapy has been proven to effectively improve upper-limb motor functi...

Value of handcrafted and deep radiomic features towards training robust machine learning classifiers for prediction of prostate cancer disease aggressiveness.

There is a growing piece of evidence that artificial intelligence may be helpful in the entire prost...

Immersive training of clinical decision making with AI driven virtual patients - a new VR platform called medical tr.AI.ning.

BACKGROUND: Medical students need to be prepared for various situations in clinical decision-making ...

Research and Evaluation of the Allosteric Protein-Specific Force Field Based on a Pre-Training Deep Learning Model.

Allosteric modulators are important regulation elements that bind the allosteric site beyond the act...

Collaborative training of medical artificial intelligence models with non-uniform labels.

Due to the rapid advancements in recent years, medical image analysis is largely dominated by deep l...

Evaluating diagnostic content of AI-generated chest radiography: A multi-center visual Turing test.

BACKGROUND: Accurate interpretation of chest radiographs requires years of medical training, and man...

Artificial intelligence: Augmenting telehealth with large language models.

This brief editorial describes an emerging area of machine learning technology called large language...