Neurology

A Machine Learning-Based Initial Difficulty Level Adjustment Method for Balance Exercise on a Trunk Rehabilitation Robot.

Trunk rehabilitation exercises such as those for remediating core stability can help improve the seated balance of patients with weakness or loss of proprioception caused by diseases such as stroke, and aid the recovery of other functions such as gait. However, there has not yet been any reported method for automatically determining the parameters that define exercise difficulty on a trunk rehabil...

Graph-Based Disease Prediction in Neuroimaging: Investigating the Impact of Feature Selection.

In biomedical machine learning, data often appear in the form of graphs. Biological systems such as protein interactions and ecological or brain networks are instances of applications that benefit from graph representations. Geometric deep learning is an arising field of techniques that has extended deep neural networks to non-Euclidean domains such as graphs. In particular, graph convolutional ne...

Identification of spinal tuberculosis subphenotypes using routine clinical data: a study based on unsupervised machine learning.

OBJECTIVE: The identification of spinal tuberculosis subphenotypes is an integral component of precision medicine. However, we lack proper study model...

Effects of end-effector robot-assisted gait training on gait ability, muscle strength, and balance in patients with spinal cord injury.

BACKGROUND: There is no randomized controlled study about the effects of end-effector robot-assisted gait training (RAGT) in patients with spinal cord...

Usability and Acceptability of Social Robot Pets Among Community-Dwelling Veterans Living With Dementia and Their Caregivers.

Social robot pets promote engagement and psychosocial well-being among older adults, yet little is known about their use among community-dwelling Vete...

Evaluation of impact of epidural volume extension on the quality of spinal anaesthesia in patients undergoing proximal femoral nailing surgeries - randomized controlled study.

INTRODUCTION: Epidural volume extension is technique aiming to mitigate spinal anaesthesia induced hypotension, by reducing the dose of local anaesthe...

Review on the Artificial Intelligence-based Nanorobotics Targeted Drug Delivery System for Brain-specific Targeting.

Contemporary medical research increasingly focuses on the blood-brain barrier (BBB) to maintain homeostasis in healthy individuals and provide solutio...

[Single-channel electroencephalogram signal used for sleep state recognition based on one-dimensional width kernel convolutional neural networks and long-short-term memory networks].

Aiming at the problem that the unbalanced distribution of data in sleep electroencephalogram(EEG) signals and poor comfort in the process of polysomno...

[Design and preliminary application of outdoor flying pigeon-robot].

Control at beyond-visual ranges is of great significance to animal-robots with wide range motion capability. For pigeon-robots, such control can be do...

[Research progress on mechanical perturbation in stroke rehabilitation].

Sensorimotor disorder can be easily caused by stroke, and there are many targeted movement rehabilitation therapies. With the development of rehabilit...

Development and validation of a deep learning algorithm based on fundus photographs for estimating the CAIDE dementia risk score.

BACKGROUND: the Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) dementia risk score is a recognised tool for dementia risk strat...

Machine learning for the prediction of acute kidney injury in critical care patients with acute cerebrovascular disease.

PURPOSE: Acute kidney injury (AKI) is a common complication and associated with a poor clinical outcome. In this study, we developed and validated a m...

An automated bedside measure for monitoring neonatal cortical activity: a supervised deep learning-based electroencephalogram classifier with external cohort validation.

BACKGROUND: Electroencephalogram (EEG) monitoring is recommended as routine in newborn neurocritical care to facilitate early therapeutic decisions an...

May Dual Transcranial Direct Current Stimulation Enhance the Efficacy of Robot-Assisted Therapy for Promoting Upper Limb Recovery in Chronic Stroke?

OBJECTIVE: To assess whether dual transcranial direct current stimulation (tDCS) may enhance the efficacy of exoskeleton robotic training on upper lim...

Towards emotionally aligned social robots for dementia: perspectives of care partners and persons with dementia.

BACKGROUND: Persons living with dementia and their care partners place a high value on aging in place and maintaining independence. Socially assistive...

Artificial Intelligence-based Detection of Epileptic Discharges from Pediatric Scalp Electroencephalograms: A Pilot Study.

We developed an artificial intelligence (AI) technique to identify epileptic discharges (spikes) in pediatric scalp electroencephalograms (EEGs). We b...

[A Case of Malignant Peripheral Nerve Sheath Tumor of the Anus Resected by Robot Assisted-APR].

An 81-year-old female visited a local hospital with complaints of anal pain. A tumor was found on the right side of her anus, and the histopathologica...

Interpretable deep learning translation of GWAS and multi-omics findings to identify pathobiology and drug repurposing in Alzheimer's disease.

Translating human genetic findings (genome-wide association studies [GWAS]) to pathobiology and therapeutic discovery remains a major challenge for Al...

Multimodal attention-based deep learning for Alzheimer's disease diagnosis.

OBJECTIVE: Alzheimer's disease (AD) is the most common neurodegenerative disorder with one of the most complex pathogeneses, making effective and clin...

Effects of a lower limb rehabilitation robot with various training modes in patients with stroke: A randomized controlled trial.

BACKGROUND: The effect of robot-assisted gait training has been demonstrated to improve gait recovery in patients with stroke. The aim of this study w...