Latest AI and machine learning research in neurology for healthcare professionals.
Falls are a major concern for people with Parkinson's disease (PwPD), but accurately assessing real-...
Understanding the generative mechanism between local field potentials (LFP) and neuronal spiking act...
OBJECTIVES: The Alberta Stroke Program Early CT Score (ASPECTS), a systematic method for assessing i...
BACKGROUND: Artificial intelligence (AI) is expected to play a greater role in neurosurgery. There i...
This study aimed to apply machine learning (ML) techniques to develop and validate a risk prediction...
In this study, we conducted an in-depth exploration of Alzheimer's Disease (AD) by integrating state...
Auditory Attention Detection (AAD) aims to detect the target speaker from brain signals in a multi-s...
BACKGROUND: The identification of factors involved in the conversion across the different Alzheimer'...
Myoelectric indices forecasting is important for muscle fatigue monitoring in wearable technologies,...
OBJECTIVE: Personal statements (PSs) and letters of recommendation (LORs) are critical components of...
The diaphragm muscle (DIAm) is the primary inspiratory muscle in mammals. In awake animals, consider...
Electroencephalography (EEG) is a non-invasive method used to track human brain activity over time. ...
OBJECTIVE: There are two major issues in the MRI image diagnosis task for Parkinson's disease. First...
Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that affects an individual's behavi...
PURPOSE: To develop a deep learning-based approach to reduce the scan time of multipool CEST MRI for...
PURPOSE: The classification of sleep stages based on Electroencephalogram (EEG) changes has signific...
Electroencephalography (EEG) has demonstrated significant value in diagnosing brain diseases. In par...
Anthropomorphized robots are increasingly integrated into human social life, playing vital roles acr...
BACKGROUND: Society is burdened with stroke-associated pneumonia (SAP) after intracerebral haemorrha...
Affect recognition in a real-world, less constrained environment is the principal prerequisite of th...
The classification of Alzheimer's disease (AD) using deep learning models is hindered by the limited...