Latest AI and machine learning research in neurology for healthcare professionals.
Due to the late manifestation of structural symptoms and symptomatic overlap, neurodegenerative diseases such as Parkinson's Disease (PD) and Alzheimer's Disease (AD) remain difficult to diagnose accurately. In order to categorize AD and PD in comparison to Healthy Controls (HC), this study suggests a multimodal classification framework that combines genetic Single Nucleotide Polymorphism (SNP) da...
OBJECTIVES: Given the heterogeneous nature of Alzheimer's Disease (AD) and its higher prevalence in females, it is crucial to understand sex-related differences in AD presentation and changes in the brain. METHODS: : This systematic review investigates sex differences in AD and summarizes key findings from neuroimaging studies over the past two decades to examine how genetics, hormones, and lifest...
Three-photon fluorescence microscopy (3PFM) enables high-resolution volumetric imaging in deep tissues but is fundamentally constrained by a trade-off...
BACKGROUND: Brain-computer interfaces (BCIs) enable direct communication between humans and machines by translating brain signals into control command...
Protein aggregation plays a central role in the pathogenesis of many neurodegenerative diseases and poses major challenges in protein engineering. A k...
Convolutional neural networks (CNNs) are widely recognized for their high precision in image classification. Nevertheless, the lack of transparency in...
CONTEXT: Post-traumatic stress disorder (PTSD) is mainly assessed through self-reports and clinician interviews, which can delay recognition and limit...
BACKGROUND: Despite evidence of group-level differences in striatal morphometry among persons with Huntington's Disease (PwHD), current models of HD p...
End-to-end EEG-based emotion recognition is attracting increasing attention due to its potential in human-computer interaction, mental health, and aff...
Objective.Accurate classification of pain levels is essential for clinical monitoring, particularly in clinical populations with limited verbal commun...
BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease, appearing to be associated with accelerated brain aging. Althoug...
OBJECTIVES: This study aims to develop a deep learning model to assist physicians in accurately classifying negative, equivocal, and positive β-amyloi...
UNLABELLED: Alzheimer’s disease (AD) is a neurodegenerative disorder that progressively deteriorates a person’s memory, as well as their ability to th...
OBJECTIVE: Pediatric scoliosis is the most prevalent spinal disorder, often leading to abnormal curvature and deformation of the spine. Early detectio...
BACKGROUND: Parkinson disease (PD) presents diagnostic challenges due to its heterogeneous motor and nonmotor manifestations. Traditional machine lear...
Precise localization of perfusion deficits in diffusion-weighted MRI (DWI) is critical for acute ischemic stroke management. However, existing deep le...
BACKGROUND: Smart patch healthcare devices are emerging as a distinct user interface in decoding the bidirectional interaction of the five sense organ...
BACKGROUND: Dementia and Parkinson's disease (PD) are among the most prevalent neurological disorders globally. Most previous research has focused on ...
BACKGROUND: Alzheimer's disease (AD) is a prevalent neurodegenerative disorder. This study aims to identify biomarkers associated with glutamine metab...
BACKGROUND AND OBJECTIVE: Aircraft pilots can be faced with a high mental workload (MW) combined with moderate hypoxia and sleep restriction. We aimed...