Work Force

[Voluntary and Adaptive Control Strategy for Ankle Rehabilitation Robot].

The control strategy of rehabilitation robots should not only adapt to patients with different level...

HNCGAT: a method for predicting plant metabolite-protein interaction using heterogeneous neighbor contrastive graph attention network.

The prediction of metabolite-protein interactions (MPIs) plays an important role in plant basic life...

The Application Artificial Intelligence-Assisted Robot System in Nursing Follow-up of Discharged Patients.

To construct a robot intelligent discharge follow-up platform and explore its application effects in...

Identifying and training deep learning neural networks on biomedical-related datasets.

This manuscript describes the development of a resources module that is part of a learning platform ...

Practical applications of artificial intelligence in dermatology residency training.

Biosignal-based Control of a Robotic Gait Training Lifter.

In this paper, we present a robotic walker that aims to encourage the patient's voluntary movement b...

Changes in pressure of strap while walking in a robotic gait training system.

Exoskeletons have been developed and widely used for medical, industrial, military applications. Sin...

Enhancement of Functional Connectivity in Frontal-Parietal Regions After BCI-Actuated Supernumerary Robotic Finger Training.

The supernumerary robotic finger (SRF) can expand human hand abilities to achieve motor augmentation...

The Effects of Robotic Exoskeleton Gait Training on Improving Walking Adaptability in Persons with MS.

The goal of the present pilot investigation is to examine the effects of 8 weeks of supervised, over...

Derm-T2IM: Harnessing Synthetic Skin Lesion Data via Stable Diffusion Models for Enhanced Skin Disease Classification using ViT and CNN.

This study explores the utilization of Dermatoscopic synthetic data generated through stable diffusi...

Multi-Scale Self-Supervised Consistency Training for Trustworthy Medical Imaging Classification.

Modern neural network models have demonstrated exceptional classification capabilities comparable to...

Design and Preliminary Evaluation of a Novel Robotic System for Anterior Shoulder Reduction.

Shoulder dislocations are the most common dislocations and there is a demand for a novel traction de...

Multidimensional feature analysis shows stratification in robotic-motor-training gains based on the level of pre-training motor impairment in stroke.

Stroke involves heterogeneity in injury and ongoing endogenous recovery, which are seldom stratified...

Contrastive Pre-Training and Multiple Instance Learning for Predicting Tumor Microsatellite Instability.

Accurate classification between tumor MicroSatellite Stability (MSS) and Instability (MSI) is crucia...

DeepSeg: A transfer-learning segmentation tool for limited sample training of nonhuman primate MRI.

Tissue segmentation of individual magnetic resonance imaging (MRI) is a fundamental step in building...

UPMatch: Enhancing Semi-Supervised Medical Image Classification through Contrastive Learning with Unreliable Pseudo Labels.

Pseudo-labeling based semi-supervised learning (SSL) framework has proven highly successful in medic...

Unravelling tumour cell diversity and prognostic signatures in cutaneous melanoma through machine learning analysis.

Melanoma, a highly malignant tumour, presents significant challenges due to its cellular heterogenei...

Integrating Artificial Intelligence Into Radiology Resident Training: A Call to Action.

Effects of training with a rehabilitation device (Rebless®) on upper limb function in patients with chronic stroke: A randomized controlled trial.

BACKGROUND: Upper limb dysfunction is one of the most common sequelae of stroke and robotic therapy ...

Development of an ontology for laparoscopic transabdominal adrenalectomy via a comprehensive modified Delphi survey and its validation on a multicentric pilot data set for surgical training and future video analysis with machine learning algorithms.

Generative AI in glioma: Ensuring diversity in training image phenotypes to improve diagnostic performance for IDH mutation prediction.

BACKGROUND: This study evaluated whether generative artificial intelligence (AI)-based augmentation ...