This study focuses on the binary classification of pediatric epilepsy seizure types as focal or generalized using Turkish electroencephalography (EEG) reports, leveraging natural language processing (NLP) and machine learning methodologies. A novel d...
Predicting epileptic seizures presents a substantial difficulty in healthcare, with considerable implications for enhancing patient outcomes and quality of life. This paper presents an explainable artificial intelligence (AI) that integrates a one-di...
Central nervous system (CNS) drugs have the highest clinical attrition, often due to CNS-related toxicities such as drug-induced seizures (DIS). Early prediction of DIS risk could reduce failure rates and optimize drug development by prioritizing tes...
Seizures in electroencephalogram (EEG) data constitute a special case of sub-sequence anomalies in multivariate data with numerous challenges. These challenges include the irregular patterns exhibited even by the same individual, making seizures diff...
Functional connectivity (FC) analyses of intracranial EEG (iEEG) signals can potentially improve the mapping of epileptic networks in drug-resistant focal epilepsy. However, it remains unclear whether FC-based metrics provide additional value beyond ...
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...
Journal of evaluation in clinical practice
Apr 1, 2025
BACKGROUND: Neonatal seizures are one of the most prevalent clinical manifestations of neurological conditions, requiring urgent intervention and detection. Machine learning (ML) and Deep Learning (DL) is an emerging promising tool for detecting and ...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jan 1, 2025
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...
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...
Nan fang yi ke da xue xue bao = Journal of Southern Medical University
Sep 20, 2024
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.
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.