International journal of computer assisted radiology and surgery
Nov 1, 2025
PURPOSE: Epilepsy surgery is a potential curative treatment for people with focal epilepsy. Intraoperative electrocorticogram (ioECoG) recordings from the brain guide neurosurgeons during resection. Accurate localization of epileptic activity and thu...
European journal of clinical pharmacology
Sep 1, 2025
PURPOSE: This study develops and compares population pharmacokinetics (PopPK) models and machine learning methods, including neural networks, to predict steady-state trough concentrations in pediatric patients and provide improved dosing recommendati...
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...
BACKGROUND: Determining whether pediatric patients with low-grade gliomas (pLGGs) have tumor-related epilepsy (GAE) is a crucial aspect of preoperative evaluation. Therefore, we aim to propose an innovative, machine learning- and deep learning-based ...
In recent years, Artificial Intelligence (AI), with a specific emphasis on attention mechanisms instead of conventional Deep Learning (DL) or Machine Learning (ML), has demonstrated significant applicability across diverse medical domains. This paper...
This study aimed to classify patients' focal (frontal, temporal, parietal, occipital), multifocal, and generalized epileptiform activities based on EEG findings using artificial intelligence models. The study included 575 patients followed in the Neu...
International journal of neural systems
Aug 1, 2025
Electroencephalography signal classification is essential for the diagnosis and monitoring of neurological disorders, with significant implications for patient treatment. Despite the progress made, existing methods face challenges such as capturing t...
Neuroscience experiments and devices are generating unprecedented volumes of data, but analyzing and validating them presents practical challenges, particularly in annotation. While expert annotation remains the gold standard, it is time consuming to...
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...
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...
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