AIMC Topic: Seizures
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Tiny Convolutional Neural Network with Supervised Contrastive Learning for Epileptic Seizure Prediction.
International journal of neural systems
Apr 28, 2025
Automatic seizure prediction based on ElectroEncephaloGraphy (EEG) ensures the safety of patients with epilepsy and mitigates anxiety. In recent years, significant progress has been made in this field. However, the predictive performance of existing ...
FusionXNet: enhancing EEG-based seizure prediction with integrated convolutional and Transformer architectures.
Journal of neural engineering
Apr 25, 2025
. Effective seizure prediction can reduce patient burden, improve clinical treatment accuracy, and lower healthcare costs. However, existing deep learning-based seizure prediction methods primarily rely on single models, which have limitations in fea...
Initial seizure episodes risk factors identification during hospitalization of ICU patients: A retrospective analysis of the eICU collaborative research database.
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Apr 21, 2025
BACKGROUND: We aimed to identify risk factors for initial seizure episodes in ICU patients using various machine learning algorithms.
Artificial intelligence for the detection of interictal epileptiform discharges in EEG signals.
Revue neurologique
Apr 10, 2025
INTRODUCTION: Over the past decades, the integration of modern technologies - such as electronic health records, cloud computing, and artificial intelligence (AI) - has revolutionized the collection, storage, and analysis of medical data in neurology...
Hardware Optimization and Implementation of a 16-Channel Neural Tree Classifier for On-Chip Closed-Loop Neuromodulation.
IEEE transactions on biomedical circuits and systems
Apr 2, 2025
This work presents the development of on-chip machine learning (ML) classifiers for implantable neuromodulation system-on-chips (SoCs), aimed at detecting epileptic seizures for closed-loop neuromodulation applications. Tree-based classifiers have ga...
Updates in Neonatal Seizures.
Clinics in perinatology
Apr 1, 2025
Neonatal seizures are a common medical emergency, necessitating prompt treatment. The most common etiologies include hypoxic-ischemic encephalopathy, ischemic stroke, and intracranial hemorrhage, with numerous other uncommon etiologies. Accurate diag...
Efficient Seizure Detection by Complementary Integration of Convolutional Neural Network and Vision Transformer.
International journal of neural systems
Mar 29, 2025
Epilepsy, as a prevalent neurological disorder, is characterized by its high incidence, sudden onset, and recurrent nature. The development of an accurate and real-time automatic seizure detection system is crucial for assisting clinicians in making ...
Select for better learning: identifying high-quality training data for a multimodal cyclic transformer.
Journal of neural engineering
Mar 25, 2025
. Tonic-clonic seizures (TCSs), which present a significant risk for sudden unexpected death in epilepsy, require accurate detection to enable effective long-term monitoring. Previous studies have demonstrated the advantages of multimodal seizure det...
EEG detection and recognition model for epilepsy based on dual attention mechanism.
Scientific reports
Mar 19, 2025
In the field of clinical neurology, automated detection of epileptic seizures based on electroencephalogram (EEG) signals has the potential to significantly accelerate the diagnosis of epilepsy. This rapid and accurate diagnosis enables doctors to pr...
Artificial intelligence (ChatGPT 4.0) vs. Human expertise for epileptic seizure and epilepsy diagnosis and classification in Adults: An exploratory study.
Epilepsy & behavior : E&B
Mar 12, 2025
AIMS: Artificial intelligence (AI) tools like ChatGPT hold promise for enhancing diagnostic accuracy and efficiency in clinical practice. This exploratory study evaluates ChatGPT's performance in diagnosing and classifying epileptic seizures, epileps...
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