A Review of Graph Theory-Based Diagnosis of Neurological Disorders Based on EEG and MRI
Graph theory analysis, as a mathematical tool, has been widely employed in studying the
connectivity of the brain to explore the structural organization. Through the computation of …
connectivity of the brain to explore the structural organization. Through the computation of …
Explainable graph neural networks for EEG classification and seizure detection in epileptic patients
Electroencephalography (EEG) is currently the most used way to accurately diagnose
epilepsy given its ability to measure hypersinchronized periods of brain activity known as …
epilepsy given its ability to measure hypersinchronized periods of brain activity known as …
The choice of evaluation metrics in the prediction of epileptiform activity
N Gromov, A Lebedeva, I Kipelkin, O Elshina… - International Conference …, 2023 - Springer
In this study, we investigate the problem of prediction of epileptiform activity from EEG data
using a deep learning approach. We implement LSTM deep neural network and study how …
using a deep learning approach. We implement LSTM deep neural network and study how …
End-to-end Stroke Imaging Analysis using Effective Connectivity and Interpretable Artificial intelligence
In this paper, we propose a reservoir computing-based and directed graph analysis pipeline.
The goal of this pipeline is to define an efficient brain representation for connectivity in stroke …
The goal of this pipeline is to define an efficient brain representation for connectivity in stroke …