Neurology

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

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Artery fragment guided approach for enhancing cerebral aneurysm detection in TOF-MRA imaging.

BACKGROUND: Cerebral aneurysms are a type of cerebrovascular disease that poses a severe threat to l...

Enhancing differentiation between unipolar and bipolar depression through integration of machine learning and electroencephalogram analysis.

To enhance the differentiation between unipolar depression (UPD) and bipolar depression (BPD), this ...

Artificial Intelligence Deep Learning Models to Predict Spaceflight Associated Neuro-ocular Syndrome (SANS).

PURPOSE: To create deep learning artificial intelligence (AI) models for predicting the development ...

Dynamic alterations of SEEG characteristics during peri-ictal period and localization of seizure onset zone.

BACKGROUND: The evolution in peri-ictal period (from pre-ictal to ictal phase) of seizures contains ...

Thalamic neural activity and epileptic network analysis using stereoelectroencephalography: a prospective study protocol.

INTRODUCTION: Epilepsy is a prevalent chronic neurological disorder, with approximately one-third of...

Deep-learning-based Partial Volume Correction in 99mTc-TRODAT-1 SPECT for Parkinson's Disease: A Preliminary Study on Clinical Translation.

Tc-TRODAT-1 SPECT is effective for the early detection of Parkinson's disease (PD). However, SPECT i...

A Comparative Study of Conventional and Tripolar EEG for High-Performance Reach-to-Grasp BCI Systems.

This study aims to enhance brain-computer interface (BCI) applications for individuals with motor im...

Detecting label noise in longitudinal Alzheimer's data with explainable artificial intelligence.

Reliable classification of cognitive states in longitudinal Alzheimer's Disease (AD) studies is crit...

Effects of concurrent HER2-directed therapy on development of cerebral radionecrosis after stereotactic radiotherapy: a systematic review.

PURPOSE: With increasing use of human epithelial growth factor receptor two (HER2)-targeted therapie...

A library of lineage-specific driver lines connects developing neuronal circuits to behavior in the ventral nerve cord.

Understanding developmental changes in neuronal lineages is crucial to elucidate how they assemble i...

Uncovering Image-Driven Subtypes with Distinct Pathology and Clinical Course in Autopsy-Confirmed Four Repeat Tauopathies.

OBJECTIVES: The four-repeat (4R) tauopathies are a group of neurodegenerative diseases, including pr...

Automated classification of seizure onset pattern using intracranial electroencephalogram signal of non-human primates.

To develop and validate a machine learning framework for the classification of distinct seizure onse...

Explainable Diagnosis Prediction through Neuro-Symbolic Integration.

Diagnosis prediction is a critical task in healthcare, where timely and accurate identification of m...

SLR: A Modified Logistic Regression Model with Sinkhorn Divergence for Alzheimer's Disease Classification.

Logistic regression is a widely used model in machine learning, particularly as a baseline for binar...

Comparison of Machine Learning Models in Predicting Mental Health Sequelae Following Concussion in Youth.

Youth who experience concussions may be at greater risk for subsequent mental health challenges, mak...

Early Alzheimer's Detection Through Voice Analysis: Harnessing Locally Deployable LLMs via , a privacy-preserving diagnostic system.

Diagnosing Alzheimer's Disease (AD) early and cost-effectively is crucial. Recent advancements in La...

An enhanced UHMWPE wear particle detection approach based on YOLOv9.

Ultra-high molecular weight polyethylene (UHMWPE) has been widely used in total joint arthroplasty f...

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