Neurology

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

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Sex-Specific Imaging Biomarkers for Parkinson's Disease Diagnosis: A Machine Learning Analysis.

This study aimed to identify sex-specific imaging biomarkers for Parkinson's disease (PD) based on m...

Cerebrospinal fluid-induced stable and reproducible SERS sensing for various meningitis discrimination assisted with machine learning.

Cerebrospinal fluid (CSF)-based pathogen or biochemical testing is the standard approach for clinica...

Deep brain stimulation and lag synchronization in a memristive two-neuron network.

In the pursuit of potential treatments for neurological disorders and the alleviation of patient suf...

A multiscale distributed neural computing model database (NCMD) for neuromorphic architecture.

Distributed neuromorphic architecture is a promising technique for on-chip processing of multiple ta...

Extracting seizure control metrics from clinic notes of patients with epilepsy: A natural language processing approach.

OBJECTIVES: Monitoring seizure control metrics is key to clinical care of patients with epilepsy. Ma...

Nonictal electroencephalographic measures for the diagnosis of functional seizures.

OBJECTIVE: Functional seizures (FS) look like epileptic seizures but are characterized by a lack of ...

Understanding Learning from EEG Data: Combining Machine Learning and Feature Engineering Based on Hidden Markov Models and Mixed Models.

Theta oscillations, ranging from 4-8 Hz, play a significant role in spatial learning and memory func...

Automatic Recognition of Multiple Emotional Classes from EEG Signals through the Use of Graph Theory and Convolutional Neural Networks.

Emotion is a complex state caused by the functioning of the human brain in relation to various event...

Intelligent Control System for Brain-Controlled Mobile Robot Using Self-Learning Neuro-Fuzzy Approach.

Brain-computer interface (BCI) provides direct communication and control between the human brain and...

Aging-related biomarkers for the diagnosis of Parkinson's disease based on bioinformatics analysis and machine learning.

Parkinson's disease (PD) is a multifactorial disease that lacks reliable biomarkers for its diagnosi...

Comorbidity-based framework for Alzheimer's disease classification using graph neural networks.

Alzheimer's disease (AD), the most prevalent form of dementia, requires early prediction for timely ...

ARViS: a bleed-free multi-site automated injection robot for accurate, fast, and dense delivery of virus to mouse and marmoset cerebral cortex.

Genetically encoded fluorescent sensors continue to be developed and improved. If they could be expr...

Subject-level spinal osteoporotic fracture prediction combining deep learning vertebral outputs and limited demographic data.

UNLABELLED: Automated screening for vertebral fractures could improve outcomes. We achieved an AUC-R...

A 25-Year Retrospective of the Use of AI for Diagnosing Acute Stroke: Systematic Review.

BACKGROUND: Stroke is a leading cause of death and disability worldwide. Rapid and accurate diagnosi...

Proteomics profiling and machine learning in nusinersen-treated patients with spinal muscular atrophy.

AIM: The availability of disease-modifying therapies and newborn screening programs for spinal muscu...

Deep Learning-Based Artificial Intelligence Can Differentiate Treatment-Resistant and Responsive Depression Cases with High Accuracy.

Although there are many treatment options available for depression, a large portion of patients wit...

An efficient ranking-based ensembled multiclassifier for neurodegenerative diseases classification using deep learning.

Neurodegenerative diseases are group of debilitating and progressive disorders that primarily affect...

Siamese based deep neural network for ADHD detection using EEG signal.

BACKGROUND: Detecting Attention-Deficit/Hyperactivity Disorder (ADHD) in children is crucial for tim...

Implementing machine learning to predict survival outcomes in patients with resected pulmonary large cell neuroendocrine carcinoma.

BACKGROUND: The post-surgical prognosis for Pulmonary Large Cell Neuroendocrine Carcinoma (PLCNEC) p...

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