Neurology

Balance biomarker for early differentiation of Parkinson's disease and multiple system atrophy with parkinsonian type.

BACKGROUND: Parkinson's disease (PD) and multiple system atrophy with parkinsonian type (MSA-P) shar...

Transcriptomic analysis and machine learning have identified shared diagnostic genes and a possible mechanism linking bipolar disorder and epilepsy.

It is well known that bipolar disorder (BD) and epilepsy (EP) are common neurological diseases. The ...

Inferring preoperative cognitive function from intraoperative electroencephalography in elderly patients using machine learning.

To develop and evaluate machine learning (ML) models that infer preoperative cognitive function from...

AI-Driven Mental Health Support for Caregivers of Individuals With Alzheimer Disease: Systematic Literature Review and Development of a Conceptual Framework.

BACKGROUND: Caregivers supporting individuals with Alzheimer disease and related dementias (AD/ADRD)...

Leveraging Naturalistic Driving Digital Biomarkers for Early Mild Cognitive Impairment Detection: Deep Learning Strategies.

BACKGROUND: Alzheimer disease and related dementias are increasing worldwide, with early detection d...

Mixture-of-Skip-Connection Deep Learning Model to Classify Stroke Severity from Diffusion Weighted Imaging Based on NIHSS.

The National Institutes of Health Stroke Scale (NIHSS) is a quantitative tool, grading neurological ...

Single-cell and multi-omics analysis identifies mitophagy-related biomarkers and therapeutic targets in ischemic stroke.

Ischemic stroke (IS) remains a leading cause of death and disability, with limited effective treatme...

Unveiling state-specific neural dynamics in migraine with and without depressive symptom: a hidden Markov model and interpretable machine learning approach.

Integrating contrastive cross-modal attention and stacked GRU for hand function rehabilitation robot control.

With the intensification of population aging and the increasing incidence of neurological diseases, ...

Unbiased quantification of persistent postural and motor deficits following spinal cord injury in mice.

Spinal cord injury (SCI) causes multifaceted postural and motor impairments that are challenging to ...

Differential quadruple pattern: A new EEG signal classification framework.

EEG signals are the letters of the brain and reflect neural activity. Abnormal EEG patterns indicate...

Forecasting-based biomedical time-series data synthesis for open data and robust AI.

The limited data availability due to strict privacy regulations and significant resource demands sev...

Neuroimaging insights into the neurophysiological subtypes of major depressive disorder.

Major depressive disorder (MDD) is a highly heterogeneous condition that limits the reliability of s...

Evaluating the potential of applying artificial intelligence in the diagnosis of major depressive disorder: Neuroimaging and clinical behavioral markers.

BACKGROUND: Consensus exists that point-of-care in scalable capabilities are required to improve the...

Using machine learning to reveal two distinct neuroanatomical subtypes of first-episode, drug-naïve major depressive disorder: Evidence from the REST-meta-MDD project.

BACKGROUND: Major depressive disorder (MDD) is a highly heterogeneous condition, complicating biomar...

Derivation of machine learning brain aging biomarkers for a set of forty thousand functional connectomes.

Various Magnetic Resonance Imaging modalities were developed to explore the brain. Among them, funct...

Improved image quality and reduced acquisition time in brain MRI using deep learning-based reconstruction: A quantitative and subjective assessment compared to standard MPRAGE in 0.55 T MRI.

PURPOSE: To assess the impact of deep learning (DL)-based image reconstruction on quantitative and s...

Force Learning in Balanced Cortical E-I Networks.

Force learning is a learning method for generating various types of complex dynamics in recurrent ne...

Automated detection of new cerebral infarctions and prognostic implications using deep learning on serial MRI.

We developed and externally validated a deep learning model to automatically detect new ischemic les...

Human-in-the-loop validation of an artificial intelligence-driven real-time prostatic capsule recognition model for nerve-sparing robot-assisted radical prostatectomy.

BACKGROUND: Nerve-sparing robot-assisted radical prostatectomy (NS-RARP) requires precise prostatic ...

High MAP3K6 Expression in Spinal Cord Injury Tissues Enhances Neuronal Apoptosis: Insights from Multi-Omics Data Integrating WGCNA, Machine Learning, and Experimental Validation.

Spinal cord injury (SCI) is a major global health issue with severe complications, yet effective bio...