Neurology

Latest AI and machine learning research in neurology for healthcare professionals.

11,973 articles
Stay Ahead - Weekly Neurology research updates
Subscribe
Browse Categories
Showing 3445-3465 of 11,973 articles
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...

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...

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...

Neuropathologist-level integrated classification of adult-type diffuse gliomas using deep learning from whole-slide pathological images.

Current diagnosis of glioma types requires combining both histological features and molecular charac...

A low-power vertical dual-gate neurotransistor with short-term memory for high energy-efficient neuromorphic computing.

Neuromorphic computing aims to emulate the computing processes of the brain by replicating the funct...

Evaluation of a novel real-time adaptive assist-as-needed controller for robot-assisted upper extremity rehabilitation following stroke.

Rehabilitation therapy plays an essential role in assisting people with stroke regain arm function. ...

A preliminary exploration into top-down and bottom-up deep-learning approaches to localising neuro-interventional point targets in volumetric MRI.

PURPOSE: Point localisation is a critical aspect of many interventional planning procedures, specifi...

Browse Categories