Neurology

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

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A Single-Channel EEG Approach for Sleep Stage-Independent Automatic Detection of REM Sleep Behavior Disorder

Rapid Eye Movement (REM) Sleep Behavior Disorder (RBD) is a parasomnia characterized by the loss of physiological muscle atonia during REM sleep, often manifesting through dream-enacting behavior. Idiopathic RBD is largely considered a prodromal stage of neurodegenerative diseases, with a conversion rate to overt α-synucleinopathies of up to 96% after 14 years. Currently, the diagnostic procedure ...

Artificial Intelligence enhanced R1 maps can improve lesion detection in focal epilepsy in children

MRI is critical for the detection of subtle cortical pathology in epilepsy surgery assessment. This can be aided by improved MRI quality and resolution using ultra-high field (7T). But poor access and long scan durations limit widespread use, particularly in a paediatric setting. AI-based learning approaches may provide similar information by enhancing data obtained with conventional MRI (3T). We ...

DeepDrug2: A Germline-focused Graph Neural Network Framework for Alzheimer’s Drug Repurposing Validated by Electronic Health Records

Alzheimer’s disease (AD) is a complex neurodegenerative disorder with limited therapeutic options. The original DeepDrug framework by Li et al. (2025)...

Assessment of the Modified Rankin Scale in Electronic Health Records with a Fine-tuned Large Language Model

The modified Rankin scale (mRS) is an important metric in stroke research, often used as a primary outcome in clinical trials and observational studie...

Neuroanatomical-Based Machine Learning Prediction of Alzheimer’s Disease Across Sex and Age

Alzheimer’s Disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and memory loss. In 2024, in the US alone, it ...

Interpretable MRI-Based Deep Learning for Alzheimer’s Risk and Progression

Timely intervention for Alzheimer’s disease (AD) requires early detection. The development of immunotherapies targeting amyloid-beta and tau underscor...

Validation of an instrumented shoe insole framework for analyzing spatiotemporal gait metrics in healthy and neurodegenerative populations

Many neurological conditions negatively affect a person’s walking quality, which is a vital aspect of their quality of life. Gait quality, through the...

Interictal Epileptiform Discharge Detection Using Probabilistic Diffusion Models and AUPRC Maximization

Recently, automated Interictal Epileptiform Discharge (IED) detection has attracted significant attention as a challenging predictive data analysis ta...

ROC Analysis of Biomarker Combinations in Fragile X Syndrome-Specific Clinical Trials: Evaluating Treatment Efficacy via Exploratory Biomarkers

Fragile X Syndrome (FXS) is a rare neurodevelopmental disorder caused by a trinucleotide repeat expansion on the 5’ untranslated region of the FMR1 ge...

Segmentation of clinical imagery for improved epidural stimulation to address spinal cord injury

Spinal cord injury (SCI) can severely impair motor and autonomic function, with long-term consequences for quality of life. Epidural stimulation has e...

USING ARTIFICIAL INTELLIGENCE TO PREDICT TREATMENT OUTCOMES IN PATIENTS WITH NEUROGENIC OVERACTIVE BLADDER AND MULTIPLE SCLEROSIS

Many women with multiple sclerosis (MS) experience neurogenic overactive bladder (NOAB) characterized by urinary frequency, urinary urgency and urgenc...

Detecting neurodegenerative changes in glaucoma using deep mean kurtosis-curve–corrected tractometry

Glaucoma is increasingly recognized as a neurodegenerative condition involving both retinal and central nervous system structures. Here, we present an...

Integrative Machine Learning Approach to Risk Prediction for Dementia and Alzheimer’s Disease

Dementia, especially Alzheimer’s disease (AD), is a major global health challenge marked by progressive cognitive impairment, behavioral changes, and ...

Electroencephalographic features of chronic subjective tinnitus: A scoping review

The goal of this scoping review is to review the scope of features from previous resting-state electroencephalography (EEG) research that have the pot...

Automated Detection of Early-Stage Dementia Using Large Language Models: A Comparative Study on Narrative Speech

The growing global burden of dementia underscores the urgent need for scalable, objective screening tools. While traditional diagnostic methods rely o...

Cross-dataset Evaluation of Dementia Longitudinal Progression Prediction Models

Accurately predicting Alzheimer’s Disease (AD) progression is useful for clinical care. The 2019 TADPOLE (The Alzheimer’s Disease Prediction Of Longit...

Integrating GWAS and Transcriptomic Data Using PrediXcan and Multimodal Deep Learning Reveals Genetic Basis and Drug Repositioning Opportunities for Alzheimer’s Disease

Alzheimer’s disease (AD), the leading cause of dementia, imposes a significant societal and economic burden; however, its complex molecular mechanisms...

SONIVA: Speech recOgNItion Validation in Aphasia

Post-stroke aphasia is a major contributor to language impairment and neuro-disability worldwide, making automated assessment a critical research prio...

Clinically reported covert cerebrovascular disease and risk of neurological disease: a whole-population cohort of 395,273 people using natural language processing

Understanding the relevance of covert cerebrovascular disease (CCD) for later health will allow clinicians to more effectively monitor and target inte...

Development of Machine Learning Algorithms Using EEG Data to Detect the Presence of Chronic Pain

Chronic pain impacts more than one in five adults in the United States (US) and the costs associated with the condition amount to hundreds of billions...

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