Neurology

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

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Showing 11041-11060 of 13,873 articles

Group-derived and individual disconnection in stroke: recovery prediction and deep graph learning

Recent advances in the treatment of acute ischemic stroke contribute to improved patient outcomes, yet the mechanisms driving long-term disease trajectory are not well-understood. Current trends in the literature emphasize the distributed disruptive impact of stroke lesions on brain network organization. While most studies use population-derived data to investigate lesion interference on healthy t...

Characteristics and Early Diagnosis of Motor Neuron Disease (MND) in 67 million individuals in England: a comparative study on phenotyping models derived by AI, Knowledge Graphs and the MND Association

Motor neuron disease (MND) is a rapidly progressive and fatal neurodegenerative condition, making early diagnosis critical for optimizing patient outcomes and care planning. Despite the existence of decade-long clinical guidelines, early diagnosis of MND remains challenging due to the lack of population-level evidence on the effectiveness of what we know and, more importantly, what we do not know....

Effects of Parietal Cathodal tDCS during Game Cue Exposure on Internet Gaming Disorder: A Randomized Double-Blind Sham-Controlled Trial

Internet Gaming Disorder (IGD) is officially listed as a behavioral addiction, exhibits high prevalence and has inadequate treatment efficacy. Targeti...

Deep Learning Prediction of Parkinson’s Disease using Remotely Collected Structured Mouse Trace Data

Parkinson’s Disease (PD) is the second most common neurodegenerative disorder globally, and current screening methods often rely on subjective evaluat...

Large-scale plasma proteomics uncovers preclinical molecular signatures of Parkinson’s disease and overlap with other neurodegenerative disorders

Parkinson’s disease (PD) remains incurable, with a long preclinical phase currently undetectable by existing methods. In the largest proteomic study i...

Automated Detection of Speech Disorders in Parkinson’s Disease using Deep Convolutional Neural Networks: A Pilot Study

Patients with Parkinson’s disease (PD) frequently exhibit deficits in functional communication due to the presence of speech disorders associated with...

Transformer Models Enable Accurate Age Prediction From Sleep Physiology

Biological age estimation, derived from physiological signatures such as brain activity, is emerging as a valuable biomarker for health and well-being...

Development and Validation of a Deep Survival Model to Predict Time-to-Seizure from Routine EEG

To develop and validate a deep survival model (EEGSurvNet) that analyzes routine EEG to predict individual seizure risk over time, comparing its perfo...

Unveiling genetic architecture of white matter microstructure through unsupervised deep representation learning of fractional anisotropy maps

Fractional anisotropy (FA) derived from diffusion MRI is a widely used marker of white matter (WM) integrity. However, conventional FA-based genetic s...

Adapting Biomedical Foundation Models for Predicting Outcomes of Anti Seizure Medications

Epilepsy affects over 50 million people worldwide, with anti-seizure medications (ASMs) as the primary treatment for seizure control. However, ASM sel...

Personalized, closed-loop deep brain stimulation for chronic pain

Chronic pain is a major healthcare problem associated with maladaptive brain circuit changes - many patients are unresponsive to all available therapi...

Antisense oligonucleotide depletion of CCDC146 is a broad-spectrum therapeutic strategy for ALS

Amyotrophic lateral sclerosis (ALS) is a heritable and incurable disease defined by the degeneration of motor neurons (MNs), yet the genetics of ALS r...

SibBMS: Siberian Brain Multiple Sclerosis Dataset with lesion segmentation and patient meta information

Multiple sclerosis (MS) is a chronic inflammatory neurodegenerative disorder of the central nervous system (CNS) and represents the leading cause of n...

Restoring Cortically Mediated Movement and Sensation in Complete Tetraplegia

Spinal cord injury (SCI) affects millions worldwide, with over half of all cases resulting in tetraplegia, where a complete injury can cause profound ...

Ensemble Machine Learning for Malaria Diagnosis in Resource-Limited Settings Using Clinical and Demographic Features

Sub-Saharan Africa continues to shoulder the heaviest burden of malaria. The 2024 WHO malaria report highlighted that Africa contributed an alarming 9...

Ultra-low-field MRI for imaging of severe multiple sclerosis: a case-controlled study

Severe multiple sclerosis (MS) presents challenges for clinical research due to mobility constraints and specialized care needs. Traditional MRI studi...

Comparative Analysis of Long COVID and Post-Vaccination Syndrome: A Cross-Sectional Study of Clinical Symptoms and Machine Learning-Based Differentiation

Long COVID is a well-documented post-viral syndrome, while post-vaccination syndrome (PVS) remains poorly characterized. Understanding their similarit...

Bridging Computational and Clinical Strategies to Improve Presurgical Identification of Epileptogenic Networks

About one third of epilepsy patients are drug-resistant. Resective surgery remains a key treatment option but depends critically on accurate identific...

Comparison of Foundation and Supervised Learning-Based Models for Detection of Referable Glaucoma from Fundus Photographs

To compare the performance of a foundation model and a supervised learning-based model for detecting referable glaucoma from fundus photographs. Evalu...

Neuroimaging Correlates of Post-Stroke Pain After Ischemic Stroke: Secondary Analysis of the INSPiRE-TMS Trial

Post-stroke pain (PSP) affects nearly half of stroke survivors, severely compromising quality of life. The causes of PSP remain underexplored, althoug...

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