Neurology

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

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Optimizing Acute Stroke Segmentation on MRI Using Deep Learning: Self-Configuring Neural Networks Provide High Performance Using Only DWI Sequences.

Segmentation of infarcts is clinically important in ischemic stroke management and prognostication. ...

Enhanced Hand Gesture Recognition with Surface Electromyogram and Machine Learning.

This study delves into decoding hand gestures using surface electromyography (EMG) signals collected...

Automated Cerebrovascular Segmentation and Visualization of Intracranial Time-of-Flight Magnetic Resonance Angiography Based on Deep Learning.

Time-of-flight magnetic resonance angiography (TOF-MRA) is a non-contrast technique used to visualiz...

Wavelet-based selection-and-recalibration network for Parkinson's disease screening in OCT images.

BACKGROUND AND OBJECTIVE: Parkinson's disease (PD) is one of the most prevalent neurodegenerative br...

Prediction of neurologic outcome after out-of-hospital cardiac arrest: An interpretable approach with machine learning.

UNLABELLED: Out-of-hospital cardiac arrest (OHCA) is a critical condition with low survival rates. I...

Machine Learning and Deep Learning Approaches in Lifespan Brain Age Prediction: A Comprehensive Review.

The concept of 'brain age', derived from neuroimaging data, serves as a crucial biomarker reflecting...

Feedback control of heart rate during robotics-assisted tilt table exercise in patients after stroke: a clinical feasibility study.

BACKGROUND: Patients with neurological disorders including stroke use rehabilitation to improve cogn...

Robustness of ML-Based Seizure Prediction Using Noisy EEG Data From Limited Channels.

Seizures pose a significant health hazard for over 50 million individuals with epilepsy worldwide, w...

Cochlear Implant Artifacts Removal in EEG-Based Objective Auditory Rehabilitation Assessment.

Cochlear implant (CI) is a neural prosthesis that can restore hearing for patients with severe to pr...

Incremental Value of Multidomain Risk Factors for Dementia Prediction: A Machine Learning Approach.

OBJECTIVE: The current evidence regarding how different predictor domains contributes to predicting ...

Joint use of population pharmacokinetics and machine learning for prediction of valproic acid plasma concentration in elderly epileptic patients.

BACKGROUND: Valproic acid (VPA) is a commonly used broad-spectrum antiepileptic drug. For elderly ep...

Detection of Pilots' Psychological Workload during Turning Phases Using EEG Characteristics.

Pilot behavior is crucial for aviation safety. This study aims to investigate the EEG characteristic...

Prognostic enrichment for early-stage Huntington's disease: An explainable machine learning approach for clinical trial.

BACKGROUND: In Huntington's disease clinical trials, recruitment and stratification approaches prima...

MFCC-CNN: A patient-independent seizure prediction model.

BACKGROUND: Automatic prediction of seizures is a major goal in the field of epilepsy. However, the ...

Accurate neuron segmentation method for one-photon calcium imaging videos combining convolutional neural networks and clustering.

One-photon fluorescent calcium imaging helps understand brain functions by recording large-scale neu...

A Deep Learning Approach to Predict Recanalization First-Pass Effect following Mechanical Thrombectomy in Patients with Acute Ischemic Stroke.

BACKGROUND AND PURPOSE: Following endovascular thrombectomy in patients with large-vessel occlusion ...

MCAS-GP: Deep Learning-Empowered Middle Cerebral Artery Segmentation and Gate Proposition.

With the fast development of AI technologies, deep learning is widely applied for biomedical data an...

A Parkinson's Auxiliary Diagnosis Algorithm Based on a Hyperparameter Optimization Method of Deep Learning.

Parkinson's disease is a common mental disease in the world, especially in the middle-aged and elder...

Automated 3D Cobb Angle Measurement Using U-Net in CT Images of Preoperative Scoliosis Patients.

To propose a deep learning framework "SpineCurve-net" for automated measuring the 3D Cobb angles fro...

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