AIMC Topic: Epilepsy

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GAN-based synthetic FDG PET images from T1 brain MRI can serve to improve performance of deep unsupervised anomaly detection models.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Research in the cross-modal medical image translation domain has been very productive over the past few years in tackling the scarce availability of large curated multi-modality datasets with the promising performance of GAN...

Automated seizure detection in epilepsy using a novel dynamic temporal-spatial graph attention network.

Scientific reports
Epilepsy is a neurological disorder characterized by recurrent seizures caused by excessive electrical discharges in brain cells, posing significant diagnostic and therapeutic challenges. Dynamic brain network analysis via electroencephalography (EEG...

Adaptive Dynamic Surface Control of Epileptor Model Based on Nonlinear Luenberger State Observer.

International journal of neural systems
Epilepsy is a prevalent neurological disorder characterized by recurrent seizures, which are sudden bursts of electrical activity in the brain. The Epileptor model is a computational model specifically created to replicate the complex dynamics of epi...

Intelligent Control to Suppress Epileptic Seizures in the Amygdala: In Silico Investigation Using a Network of Izhikevich Neurons.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Closed-loop electricalstimulation of brain structures is one of the most promising techniques to suppress epileptic seizures in drug-resistant refractory patients who are also ineligible to ablative neurosurgery. In this work, an intelligent controll...

ML-based Models as a Strategy to Discover Novel Antiepileptic Drugs Targeting Sodium Receptor Channel.

Current topics in medicinal chemistry
BACKGROUND: Epilepsy remains the most common and chronic disorder demanding longterm management. The impact of epilepsy disease is a cause of great concern and has resulted in efforts to develop treatment for epilepsy. It occurs due to an increase in...

Smart Seizure Detection System: Machine Learning Based Model in Healthcare IoT.

Current aging science
BACKGROUND: Epilepsy, the tendency to have recurrent seizures, can have various causes, including brain tumors, genetics, stroke, brain injury, infections, and developmental disorders. Epileptic seizures are usually transient events. They normally le...

[An autoencoder model based on one-dimensional neural network for epileptic EEG anomaly detection].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
OBJECTIVE: We propose an autoencoder model based on a one-dimensional convolutional neural network (1DCNN) as the feature extraction network for efficient detection of epileptic EEG anomalies.

Interictal Epileptiform Discharge Detection Using Time-Frequency Analysis and Transfer Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Interictal epileptiform discharges (IEDs) are electrophysiological events that intermittently occur in between seizures in Epilepsy patients. Automated detection of IEDs is crucial for assisting clinicians in epilepsy diagnosis as they can help ident...

Automated Intraoperative Visual Detection of Pediatric Epileptogenic Brain Lesions Using a Machine Learning Classifier.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
450,000 children with epilepsy in the United States suffer lifelong disability and are at risk of sudden death. Surgical treatment of epilepsy is limited by the ability to visually discriminate between normal and abnormal brain tissue using visual li...

LightIED: Explainable AI with Light CNN for Interictal Epileptiform Discharge Detection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Interictal epileptic discharge (IED) detection from electroencephalography (EEG) is an important but difficult step in the epilepsy diagnosis. To reduce the workload of doctors, some diagnostic auxiliary methods based on deep learning have been propo...