Cargando…
Evaluation of Feature Selection Methods for Classification of Epileptic Seizure EEG Signals
Epilepsy is a disease that decreases the quality of life of patients; it is also among the most common neurological diseases. Several studies have approached the classification and prediction of seizures by using electroencephalographic data and machine learning techniques. A large diversity of feat...
Autores principales: | Sánchez-Hernández, Sergio E., Salido-Ruiz, Ricardo A., Torres-Ramos, Sulema, Román-Godínez, Israel |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9031940/ https://www.ncbi.nlm.nih.gov/pubmed/35459052 http://dx.doi.org/10.3390/s22083066 |
Ejemplares similares
-
Pneumonia and Pulmonary Thromboembolism Classification Using Electronic Health Records
por: Siordia-Millán, Sinhue, et al.
Publicado: (2022) -
On DNA numerical representations for genomic similarity computation
por: Mendizabal-Ruiz, Gerardo, et al.
Publicado: (2017) -
Classification of epileptic seizure using feature selection based on fuzzy membership from EEG signal
por: Lee, Sang-Hong
Publicado: (2021) -
Genomic signal processing for DNA sequence clustering
por: Mendizabal-Ruiz, Gerardo, et al.
Publicado: (2018) -
Classification of single-channel EEG signals for epileptic seizures detection based on hybrid features
por: Lu, Yanan, et al.
Publicado: (2018)