Neurology

Deep learning based on susceptibility-weighted MR sequence for detecting cerebral microbleeds and classifying cerebral small vessel disease.

BACKGROUND: Cerebral microbleeds (CMBs) serve as neuroimaging biomarkers to assess risk of intracere...

Correlation between 25-hydroxy-vitamin D and Parkinson's disease.

BACKGROUND: Previous cross-sectional studies have shown that Parkinson's disease (PD) patients have ...

Two-timescale projection neural networks in collaborative neurodynamic approaches to global optimization and distributed optimization.

In this paper, we propose a two-timescale projection neural network (PNN) for solving optimization p...

Natural language processing for identification of refractory status epilepticus in children.

OBJECTIVE: Pediatric status epilepticus is one of the most frequent pediatric emergencies, with high...

Proposal of neural network model for neurocognitive rehabilitation and its comparison with fuzzy expert system model.

This article focuses on the development of algorithms for a smart neurorehabilitation system, whose ...

Detection and classification of adult epilepsy using hybrid deep learning approach.

The electroencephalogram (EEG) has emerged over the past few decades as one of the key tools used by...

Brain-computer interface for robot control with eye artifacts for assistive applications.

Human-robot interaction is a rapidly developing field and robots have been taking more active roles ...

Class-Balanced Deep Learning with Adaptive Vector Scaling Loss for Dementia Stage Detection.

Alzheimer's disease (AD) leads to irreversible cognitive decline, with Mild Cognitive Impairment (MC...

Automatic selection of spoken language biomarkers for dementia detection.

This paper analyzes diverse features extracted from spoken language to select the most discriminativ...

Artificial intelligence for dementia prevention.

INTRODUCTION: A wide range of modifiable risk factors for dementia have been identified. Considerabl...

Reply to Letter to the Editor: "Accurate measurement of magnetic resonance parkinsonism index by a fully automatic and deep learning quantification pipeline".

Deep Learning-Based Classification of Epileptic Electroencephalography Signals Using a Concentrated Time-Frequency Approach.

ConceFT (concentration of frequency and time) is a new time-frequency (TF) analysis method which com...

c-Diadem: a constrained dual-input deep learning model to identify novel biomarkers in Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is an incurable, debilitating neurodegenerative disorder. Curre...

Application of metabolomics in diagnostics and differentiation of meningitis: A narrative review with a critical approach to the literature.

Due to its high mortality rate associated with various life-threatening sequelae, meningitis poses a...

Electroencephalographic abnormalities in children with type 1 diabetes mellitus: a prospective study.

BACKGROUND/AIM: The aim herein was to investigate epileptiform discharges on electroencephalogram (E...

Large language models: Are artificial intelligence-based chatbots a reliable source of patient information for spinal surgery?

PURPOSE: Large language models (LLM) have recently attracted attention because of their enormous per...

The role of robot-assisted training on rehabilitation outcomes in Parkinson's disease: a systematic review and meta-analysis.

PURPOSE: The study aims to assess the efficacy of robot-assisted rehabilitation training on upper an...

An interpretable ensemble learning model facilitates early risk stratification of ischemic stroke in intensive care unit: Development and external validation of ICU-ISPM.

Ischemic stroke (IS) is a common and severe condition that requires intensive care unit (ICU) admiss...

A highly integrated bionic hand with neural control and feedback for use in daily life.

Restoration of sensorimotor function after amputation has remained challenging because of the lack o...

Plantar somatosensory restoration enhances gait, speed perception, and motor adaptation.

Lower limb loss is a major insult to the body's nervous and musculoskeletal systems. Despite technol...

A robot-based interception task to quantify upper limb impairments in proprioceptive and visual feedback after stroke.

BACKGROUND: A key motor skill is the ability to rapidly interact with our dynamic environment. Human...