Neurology

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

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Novel Robotic Balloon-Based Device for Wrist-Extension Therapy of Hemiparesis Stroke Patients.

Upper-limb paresis is one of the main complications after stroke. It is commonly associated with imp...

Epilepsy surgery candidate identification with artificial intelligence: An implementation study.

BACKGROUND: To (a) evaluate the effect of a machine learning algorithm in the identification of pati...

Towards Rapid and Low-Cost Stroke Detection Using SERS and Machine Learning.

Stroke affects approximately 12 million individuals annually, necessitating swift diagnosis to avert...

Identification of UBE2N as a biomarker of Alzheimer's disease by combining WGCNA with machine learning algorithms.

Alzheimer's disease (AD) is the most common cause of dementia, emphasizing the critical need for the...

Traditional and machine learning models for predicting haemorrhagic transformation in ischaemic stroke: a systematic review and meta-analysis.

BACKGROUND: Haemorrhagic transformation (HT) is a severe complication after ischaemic stroke, but id...

Neurobiologically interpretable causal connectome for predicting young adult depression: A graph neural network study.

BACKGROUND: There is a surprising lack of neuroimaging studies of depression that not only identify ...

Unsupervised learning from EEG data for epilepsy: A systematic literature review.

BACKGROUND AND OBJECTIVES: Epilepsy is a neurological disorder characterized by recurrent epileptic ...

Integrating NLP and LLMs to discover biomarkers and mechanisms in Alzheimer's disease.

Alzheimer's disease (AD) is a progressive neurological condition characterized by cognitive decline,...

Utilizing 12-lead electrocardiogram and machine learning to retrospectively estimate and prospectively predict atrial fibrillation and stroke risk.

BACKGROUND: The stroke risk in patients with subclinical atrial fibrillation (AF) is underestimated....

Organic Artificial Nerves: Neuromorphic Robotics and Bioelectronics.

Neuromorphic electronics are inspired by the human brain's compact, energy-efficient nature and its ...

Machine learning based seizure classification and digital biosignal analysis of ECT seizures.

While artificial intelligence has received considerable attention in various medical fields, its app...

Enhanced in silico QSAR-based screening of butyrylcholinesterase inhibitors using multi-feature selection and machine learning.

Butyrylcholinesterase inhibition offers one of the formulated solutions to tackle the aggravating sy...

Inertial primal-dual projection neurodynamic approaches for constrained convex optimization problems and application to sparse recovery.

Second-order (inertial) neurodynamic approaches are excellent tools for solving convex optimization ...

Integrating manual preprocessing with automated feature extraction for improved rodent seizure classification.

HYPOTHESIS/OBJECTIVE: Rodent models of epilepsy can help with the search for more effective drug can...

Artificial intelligence versus neurologists: A comparative study on multiple sclerosis expertise.

INTRODUCTION: Multiple sclerosis (MS) is an autoimmune neurodegenerative disease affecting the centr...

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