Neurology

Seizures

Latest AI and machine learning research in seizures 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 ...

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 ...

Interictal Epileptiform Discharge Detection Using Probabilistic Diffusion Models and AUPRC Maximization

Recently, automated Interictal Epileptiform Discharge (IED) detection has attracted significant atte...

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 elect...

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...

AI-Driven Personalization of Dual Antiplatelet Therapy Duration Post-PCI: A Novel Approach Balancing Ischemic and Bleeding Risks

Precision-guided dual antiplatelet therapy (DAPT) duration post-percutaneous coronary intervention (...

Event-based seizure detection in human iEEG with neuromorphic hardware

Epilepsy is a neurological disorder that affects approximately 1% of the global population. The curr...

Effects of Parietal Cathodal tDCS during Game Cue Exposure on Internet Gaming Disorder: A Randomized Double-Blind Sham-Controlled Trial

Internet Gaming Disorder (IGD) is officially listed as a behavioral addiction, exhibits high prevale...

Transformer Models Enable Accurate Age Prediction From Sleep Physiology

Biological age estimation, derived from physiological signatures such as brain activity, is emerging...

Development and Validation of a Deep Survival Model to Predict Time-to-Seizure from Routine EEG

To develop and validate a deep survival model (EEGSurvNet) that analyzes routine EEG to predict indi...

Adapting Biomedical Foundation Models for Predicting Outcomes of Anti Seizure Medications

Epilepsy affects over 50 million people worldwide, with anti-seizure medications (ASMs) as the prima...

Personalized, closed-loop deep brain stimulation for chronic pain

Chronic pain is a major healthcare problem associated with maladaptive brain circuit changes - many ...

Bridging Computational and Clinical Strategies to Improve Presurgical Identification of Epileptogenic Networks

About one third of epilepsy patients are drug-resistant. Resective surgery remains a key treatment o...

Machine Learning-Based Reconstruction of 2D MRI for Quantitative Morphometry in Epilepsy

Structural neuroimaging analyses require ‘research quality’ images, acquired with costly MRI acquisi...

Evaluating the Generalizability of EEG-Based AI Models in Alzheimer’s and Dementia Diagnosis

We thoroughly investigated the generalizability of deep learning models trained on electroencephalog...

Interpretable Transformer Models for rs-fMRI Epilepsy Classification and Biomarker Discovery

Automated interpretation of resting-state fMRI (rs-fMRI) for epilepsy diagnosis remains a challenge....

Neuromorphic Neuromodulation: A Low-Power Edge-Training Framework for the Future of Personalized and Closed-Loop Neurostimulation

Epilepsy affects approximately 1% of the global population, with 30-40% of cases resistant to conven...

Objective Assessment of Microperimetry Exam Using EEG Signals

To test the hypothesis that deep learning can decode single-trial cortical responses from electroenc...

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