Cargando…
A Comprehensive Machine-Learning-Based Software Pipeline to Classify EEG Signals: A Case Study on PNES vs. Control Subjects
The diagnosis of psychogenic nonepileptic seizures (PNES) by means of electroencephalography (EEG) is not a trivial task during clinical practice for neurologists. No clear PNES electrophysiological biomarker has yet been found, and the only tool available for diagnosis is video EEG monitoring with...
Autores principales: | Varone, Giuseppe, Gasparini, Sara, Ferlazzo, Edoardo, Ascoli, Michele, Tripodi, Giovanbattista Gaspare, Zucco, Chiara, Calabrese, Barbara, Cannataro, Mario, Aguglia, Umberto |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7071461/ https://www.ncbi.nlm.nih.gov/pubmed/32102437 http://dx.doi.org/10.3390/s20041235 |
Ejemplares similares
-
Permutation Entropy-Based Interpretability of Convolutional Neural Network Models for Interictal EEG Discrimination of Subjects with Epileptic Seizures vs. Psychogenic Non-Epileptic Seizures
por: Lo Giudice, Michele, et al.
Publicado: (2022) -
Information Theoretic-Based Interpretation of a Deep Neural Network Approach in Diagnosing Psychogenic Non-Epileptic Seizures
por: Gasparini, Sara, et al.
Publicado: (2018) -
EEG-based classification of epilepsy and PNES: EEG microstate and functional brain network features
por: Ahmadi, Negar, et al.
Publicado: (2020) -
A Machine Learning Approach Involving Functional Connectivity Features to Classify Rest-EEG Psychogenic Non-Epileptic Seizures from Healthy Controls
por: Varone, Giuseppe, et al.
Publicado: (2021) -
Perceptions in PNES: A Bidirectional Problem
por: Dworetzky, Barbara
Publicado: (2019)