Neurology

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

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Deep learning-based decoding of axonal ultrastructure in gene-edited mice using electron microscopy imaging

Myelin forms an insulating sheath around axons enabling both rapid and energy-efficient conduction of action potentials and myelin abnormalities or loss can lead to severe motor, sensory, and cognitive impairment. While electron microscopy can resolve multiple axonal components that are affected myelin, their large-scale quantitative analysis is both difficult and time consuming. To overcome such ...

Automated quantification of cerebral microbleeds for ARIA-H monitoring in Aging and Alzheimer's Disease: A multicenter deep learning validation

We trained a self-configuring nnU-Net model for CMB segmentation in a heterogeneous multicenter sample (n=264), including 1.5T and 3T field strengths, SWI and T2*-GRE sequences, and community and clinical cohorts. Model performance was evaluated using 5-fold cross-validation with a focus on object-level detection metrics. Real-world performance was evaluated on scans from an unseen dataset of peop...

Automated Segmentation of Cerebral Arteries on Three-Dimensional Rotational Angiography Using nnUNet v2: Prospective Validation with Quantitative Metrics and Expert Qualitative Assessment

Background: Three-dimensional visualization and quantitative analysis of cerebral arteries on 3DRA are central to endovascular treatment planning, dev...

AI-based Psychiatric Prediction in Youth: Neuroimaging Provides Minimal Gains Beyond Confounds

Recent advances in artificial intelligence (AI) have raised interest in its potential to similarly progress biological psychiatry. This study investig...

Automated sleep scoring in hibernating and non-hibernating American black bears

Hibernating bears show remarkable metabolic suppression. Their decline in core body temperature (Tb) is moderate(from 38{degrees}C to 30-35{degrees}C)...

CSV-ViT: A Vision Transformer with the Variable-sized Cortical Supervertices for Detection of Alzheimer's Disease Pathologies

Confirming Alzheimer's disease (AD) typically relies on positron emission tomography (PET), which remains costly and invasive, motivating the use of s...

May 26 2026 2605.26514v1
Normative modeling for quantitative brain MRI phenotyping and biomarker discovery for pediatric leukodystrophies

Importance: Leukodystrophies are a heterogeneous group of genetic disorders affecting the white matter of the brain, often presenting with overlapping...

Cross-Model Variability in Large Language Model Triage Behavior for Potential Stroke Symptoms

Background: Stroke is a time-sensitive neurological emergency in which early EMS activation and presentation to definitive care are cornerstones of ef...

A Multimodal Framework for Dementia Detection via Linguistic and Acoustic Representation Learning

Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the leading cause of dementia, affecting memory, reasoning, communication, an...

May 25 2026 2605.25540v1
ARMA-C3: A Contrastive ARMA Convolutional Framework for Unsupervised and Semi-supervised Classification

In biomedical and neurodegenerative disorders, accurate and early disease identification remains challenging due to the scarcity of labeled data and t...

May 25 2026 2605.25657v1
Causal Network Mapping of sEEG Identifies Compact Epileptogenic Targets Concordant with Seizure Freedom: Multicenter Validation in 60 Patients

Background and Purpose: Drug resistant epilepsy (DRE) affects approximately 15 million people worldwide, and surgery remains the only curative option....

Multimodal MRI and Machine Learning Uncovers Distinct Progression Patterns in Friedreich Ataxia

Background Friedreich ataxia (FRDA) is a rare neurodegenerative disorder with substantial heterogeneity in clinical presentation and progression, comp...

Predicting Autopsy-Confirmed Neuropathology across Clinical, Neuroimaging, and CSF Biomarkers using Machine Learning

Accurate in vivo prediction of neuropathology is critical for advancing diagnosis and treatment of Alzheimer's disease and related dementias (ADRDs). ...

MASHA: A Multi-Agent System for Healthcare Sentiment Analysis Using AI for Migraine Detection in Arabic Tweets

Migraine detection and sentiment analysis in healthcare have become increasingly important, particularly with the rise of social media platforms like ...

Deep Learning and Machine Learning for Early Detection of Alzheimer's Disease: A Systematic Review and Meta-Analysis

Alzheimer's disease is a progressive neurodegenerative disorder that poses a growing global public health challenge. Early and accurate diagnosis is c...

A Competitive Framework for Modeling EEG Microstate Durations

Background. This study examines a competition based model (Cmodel) designed to capture the temporal dynamics of successive brain microstates derived f...

Seizure-Semiology-Suite (S3): A Clinically Multimodal Dataset, Benchmark, and Models for Seizure Semiology Understanding

While Multimodal Large Language Models (MLLMs) have demonstrated remarkable proficiency in general video understanding, their capacity to interpret in...

May 21 2026 2605.21852v1
Interpretable Symptom-Based Machine Learning for Parkinson's Disease Prediction: A Feasibility Study

Background: Parkinson's disease (PD) has a prolonged prodromal phase during which non-motor symptoms (NMS) may emerge years before the appearance of c...

Computational Transformation of Chemical Biology for Precision Therapeutics: Facilitating In-Silico Study of Role of Cuproptosis in Early Detection of Alzheimers Disease

Background: Alzheimers disease (AD) is a multifactorial neurodegenerative disorder in which copper dyshomeostasis, mitochondrial stress, oxidative inj...

Benchmarking General-Purpose and Medical AI Large Language Models for Clinical Assessment and Management in Parkinson's Disease

Background: The clinical applicability of large language models (LLMs) in Parkinson's disease (PD) management remains insufficiently characterized, pa...

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