Neurology

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

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Showing 9741-9760 of 13,873 articles

A Deep-Learning Atlas of XPO1-Mediated Nuclear Export at Proteome Scale

Exportin 1 (XPO1/CRM1) is the principal nuclear export receptor for cargos bearing hydrophobic nuclear export sequences (NESs). Dysregulation of XPO1-dependent export is implicated in cancer, neurodegeneration, and other diseases, yet a comprehensive view of XPO1 function remains limited by the poor reliability of sequence-based NES prediction. Existing predictors are largely derived from a small ...

Altered EEG markers of reward learning during abstinence in alcohol dependence: a probabilistic reversal learning study

Maladaptive reward learning and decision-making circuity are key factors in the onset and progression of alcohol use disorder and have therefore emerged as key targets for neuropsychological and pharmacological interventions. Probabilistic reversal learning studies have consistently reported impaired learning in recently detoxified alcohol dependent (AD) participants. However, the neural and behav...

Preventing Data Leakage in EEG-Based Survival Prediction: A Two-Stage Embedding and Transformer Framework

Deep learning models have shown promise in EEG-based outcome prediction for comatose patients after cardiac arrest, but their reliability is often com...

Mar 26 2026 2603.25923v1
EEG-SSFormer: Towards a Robust Mamba-Based Architecture for Dementia Detection from Resting State Electroencephalography

Resting-state electroencephalography (rs-EEG) offers a cost effective and portable alternative to conventional neuroimaging for dementia screening, ye...

Spectral and non-spectral EEG measures in the prediction of working memory task performance and psychopathology

Working memory (WM) supports the temporary maintenance of goal-relevant information and is disrupted across many neuropsychiatric disorders. We examin...

NeuroVLM-Bench: Evaluation of Vision-Enabled Large Language Models for Clinical Reasoning in Neurological Disorders

Recent advances in multimodal large language models enable new possibilities for image-based decision support. However, their reliability and operatio...

Mar 25 2026 2603.24846v1
Medical errors in large language models revealed using 1,000 synthetic clinical transcripts

Current clinical evaluations of large language models (LLMs) rely on datasets which fail to reflect real-world medical complexity. We developed a high...

Stimulus-Driven Leakage in Naturalistic Neuroimaging

This article elucidates a methodological pitfall of cross-validation for evaluating predictive models applied to naturalistic neuroimaging data---name...

AD-Reasoning: Multimodal Guideline-Guided Reasoning for Alzheimer's Disease Diagnosis

Alzheimer's disease (AD) diagnosis requires integrating neuroimaging with heterogeneous clinical evidence and reasoning under established criteria, ye...

Mar 25 2026 2603.24059v1
Modeling Spatiotemporal Neural Frames for High Resolution Brain Dynamic

Capturing dynamic spatiotemporal neural activity is essential for understanding large-scale brain mechanisms. Functional magnetic resonance imaging (f...

Mar 25 2026 2603.24176v1
AI Generalisation Gap In Comorbid Sleep Disorder Staging

Accurate sleep staging is essential for diagnosing OSA and hypopnea in stroke patients. Although PSG is reliable, it is costly, labor-intensive, and m...

Mar 24 2026 2603.23582v1
Learning Cross-Joint Attention for Generalizable Video-Based Seizure Detection

Automated seizure detection from long-term clinical videos can substantially reduce manual review time and enable real-time monitoring. However, exist...

Mar 24 2026 2603.23757v1
A deep-learning based biomarker of systemic cellular senescence burden to predict mortality and health outcomes

Introduction: The accumulation of senescent cells is a recognized hallmark of biological aging and is associated with the onset of multiple chronic me...

Feasibility study on a Noninvasive Assessment of ALS Patient Emotional State

This study addresses the need for objective, real-time assessment of emotional responsiveness and coping strategies in individuals with Amyotrophic La...

Vision-based Deep Learning Analysis of Unordered Biomedical Tabular Datasets via Optimal Spatial Cartography

Tabular data are central to biomedical research, from liquid biopsy and bulk and single-cell transcriptomics to electronic health records and phenotyp...

Mar 24 2026 2603.22675v1
Cerebra: A Multidisciplinary AI Board for Multimodal Dementia Characterization and Risk Assessment

Modern clinical practice increasingly depends on reasoning over heterogeneous, evolving, and incomplete patient data. Although recent advances in mult...

Mar 23 2026 2603.21597v2
A Clinical Guideline-Grounded Hybrid Agentic Framework for Holistic Epilepsy Management.

Epilepsy is a chronic neurological disorder requiring multi-faceted management, including seizure detection, syndrome diagnosis, prognostication, anti...

Domain-adapted language model using reinforcement learning for various dementias

Large language models excel at processing complex clinical data and advanced reasoning, yet domain-specific adaptation is essential to realize their f...

A Multidisciplinary AI Board for Multimodal Dementia Characterization and Risk Assessment

Modern clinical practice increasingly depends on reasoning over heterogeneous, evolving, and incomplete patient data. Although recent advances in mult...

Mar 23 2026 2603.21597v1
Cycle Inverse-Consistent TransMorph: A Balanced Deep Learning Framework for Brain MRI Registration

Deformable image registration plays a fundamental role in medical image analysis by enabling spatial alignment of anatomical structures across subject...

Mar 23 2026 2603.21760v1
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