Neurology

The efficacy of hybrid neuroprostheses in the rehabilitation of upper limb impairment after stroke, a narrative and systematic review with a meta-analysis.

BACKGROUND: Paresis of the upper limb (UL) is the most frequent impairment after a stroke. Hybrid neuroprostheses, i.e., the combination of robots and electrical stimulation, have emerged as an option to treat these impairments.

Self-Attentive Channel-Connectivity Capsule Network for EEG-Based Driving Fatigue Detection.

Deep neural networks have recently been successfully extended to EEG-based driving fatigue detection. Nevertheless, most existing models fail to reveal the intrinsic inter-channel relations that are known to be beneficial for EEG-based classification. Additionally, these models require substantial data for training, which is often impractical due to the high cost of data collection. To simultaneou...

Developing and deploying deep learning models in brain magnetic resonance imaging: A review.

Magnetic resonance imaging (MRI) of the brain has benefited from deep learning (DL) to alleviate the burden on radiologists and MR technologists, and ...

Deep-learning detection of mild cognitive impairment from sleep electroencephalography for patients with Parkinson's disease.

Parkinson's disease which is the second most prevalent neurodegenerative disorder in the United States is a serious and complex disease that may progr...

Potential Facilitators of and Barriers to Implementing the MINI Robot in Community-Based Meeting Centers for People With Dementia and Their Carers in the Netherlands and Spain: Explorative Qualitative Study.

BACKGROUND: Social robots, as a form of digital health technologies, are used to support emotional, cognitive, and physical care and have shown promis...

An Intelligent Rehabilitation Assessment Method for Stroke Patients Based on Lower Limb Exoskeleton Robot.

The 6-min walk distance (6MWD) and the Fugl-Meyer assessment lower-limb subscale (FMA-LE) of the stroke patients provide the critical evaluation stand...

Evaluation of sexual function after robot-assisted radical prostatectomy: A farewell to IIEF questionnaire.

Longevity with localized prostate cancer (PCa) has been achieved, and the contribution of robot-assisted radical prostatectomy (RARP) to cancer contro...

An appraisal of the performance of AI tools for chronic stroke lesion segmentation.

Automated demarcation of stoke lesions from monospectral magnetic resonance imaging scans is extremely useful for diverse research and clinical applic...

Multi-dimensional deep learning drives efficient discovery of novel neuroprotective peptides from walnut protein isolates.

Neurodegenerative diseases, such as Alzheimer's and Parkinson's, are multi-factor induced neurological disorders that require management from multiple...

An alternative method of SNP inclusion to develop a generalized polygenic risk score analysis across Alzheimer's disease cohorts.

INTRODUCTION: Polygenic risk scores (PRSs) have great clinical potential for detecting late-onset diseases such as Alzheimer's disease (AD), allowing ...

Automated diagnosis of 7 canine skin tumors using machine learning on H&E-stained whole slide images.

Microscopic evaluation of hematoxylin and eosin-stained slides is still the diagnostic gold standard for a variety of diseases, including neoplasms. N...

Externally validated deep learning model to identify prodromal Parkinson's disease from electrocardiogram.

Little is known about electrocardiogram (ECG) markers of Parkinson's disease (PD) during the prodromal stage. The aim of the study was to build a gene...

Artificial Intelligence for context-aware surgical guidance in complex robot-assisted oncological procedures: An exploratory feasibility study.

INTRODUCTION: Complex oncological procedures pose various surgical challenges including dissection in distinct tissue planes and preservation of vulne...

Machine learning and biological evaluation-based identification of a potential MMP-9 inhibitor, effective against ovarian cancer cells SKOV3.

MMP-9, also known as gelatinase B, is a zinc-metalloproteinase family protein that plays a key role in the degradation of the extracellular matrix (EC...

Memristive Neural Networks for Predicting Seizure Activity.

UNLABELLED: is to assess the possibilities of predicting epileptiform activity using the neuronal activity data recorded from the hippocampus and med...

Effect of Lower Limb Exoskeleton on the Modulation of Neural Activity and Gait Classification.

Neurorehabilitation with robotic devices requires a paradigm shift to enhance human-robot interaction. The coupling of robot assisted gait training (R...

An extended clinical EEG dataset with 15,300 automatically labelled recordings for pathology decoding.

Automated clinical EEG analysis using machine learning (ML) methods is a growing EEG research area. Previous studies on binary EEG pathology decoding ...

Validation of deep learning techniques for quality augmentation in diffusion MRI for clinical studies.

The objective of this study is to evaluate the efficacy of deep learning (DL) techniques in improving the quality of diffusion MRI (dMRI) data in clin...

Technological Advances in Stroke Rehabilitation: Robotics and Virtual Reality.

Robotic technology and virtual reality (VR) have been widely studied technologies in stroke rehabilitation over the last few decades. Both technologie...

Early Detection of Optic Nerve Changes on Optical Coherence Tomography Using Deep Learning for Risk-Stratification of Papilledema and Glaucoma.

BACKGROUND: The use of artificial intelligence is becoming more prevalence in medicine with numerous successful examples in ophthalmology. However, mu...