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Epilepsy

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A Multimodal AI System for Out-of-Distribution Generalization of Seizure Identification.

IEEE journal of biomedical and health informatics
Artificial intelligence (AI) and health sensory data-fusion hold the potential to automate many laborious and time-consuming processes in hospitals or ambulatory settings, e.g. home monitoring and telehealth. One such unmet challenge is rapid and acc...

A method for AI assisted human interpretation of neonatal EEG.

Scientific reports
The study proposes a novel method to empower healthcare professionals to interact and leverage AI decision support in an intuitive manner using auditory senses. The method's suitability is assessed through acoustic detection of the presence of neonat...

EEG-Based Epileptic Seizure Detection via Machine/Deep Learning Approaches: A Systematic Review.

Computational intelligence and neuroscience
Epileptic seizure is one of the most chronic neurological diseases that instantaneously disrupts the lifestyle of affected individuals. Toward developing novel and efficient technology for epileptic seizure management, recent diagnostic approaches ha...

Deep-learning-based seizure detection and prediction from electroencephalography signals.

International journal for numerical methods in biomedical engineering
Electroencephalography (EEG) is among the main tools used for analyzing and diagnosing epilepsy. The manual analysis of EEG must be conducted by highly trained clinicians or neuro-physiologists; a process that is considered to have a comparatively lo...

Engineering nonlinear epileptic biomarkers using deep learning and Benford's law.

Scientific reports
In this study, we designed two deep neural networks to encode 16 features for early seizure detection in intracranial EEG and compared them and their frequency responses to 16 widely used engineered metrics to interpret their properties: epileptogeni...

Robot-assisted, real-time, MRI-guided laser interstitial thermal therapy for pediatric patients with hypothalamic hamartoma: surgical technique, pitfalls, and initial results.

Journal of neurosurgery. Pediatrics
OBJECTIVE: Real-time, MRI-guided laser interstitial thermal therapy (MRgLITT) has been reported as a safe and effective technique for the treatment of epileptogenic foci in children and adults. After the recent approval of MRgLITT by the European Med...

Prediction Value of Epilepsy Secondary to Inferior Cavity Hemorrhage Based on Scalp EEG Wave Pattern in Deep Learning.

Journal of healthcare engineering
OBJECTIVE: To search the predictive value of epilepsy secondary to acute subarachnoid hemorrhage (aSAH) based on EEG wave pattern in deep learning.

Accurate identification of EEG recordings with interictal epileptiform discharges using a hybrid approach: Artificial intelligence supervised by human experts.

Epilepsia
OBJECTIVE: To evaluate the diagnostic performance of artificial intelligence (AI)-based algorithms for identifying the presence of interictal epileptiform discharges (IEDs) in routine (20-min) electroencephalography (EEG) recordings.

An interactive framework for the detection of ictal and interictal activities: Cross-species and stand-alone implementation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Despite advances on signal analysis and artificial intelligence, visual inspection is the gold standard in event detection on electroencephalographic recordings. This process requires much time of clinical experts on both an...

Automated seizure activity tracking and onset zone localization from scalp EEG using deep neural networks.

PloS one
We propose a novel neural network architecture, SZTrack, to detect and track the spatio-temporal propagation of seizure activity in multichannel EEG. SZTrack combines a convolutional neural network encoder operating on individual EEG channels with re...