Effective classification for neonatal brain injury using EEG feature selection based on elastic net regression and improved crow search algorithm
Neonatal brain injury carries the risk of neurological sequelae such as epileptic seizures, cerebral palsy, intellectual disability, and even death. Classification methods based on electroencephalography (EEG) signals and machine learning algorithms are crucial for assessing neonatal brain injury. H...
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| Auteurs principaux: | , , , , , , |
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| Format: | Article |
| Langue: | anglais |
| Publié: |
PeerJ Inc.
2025-07-01
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| Collection: | PeerJ Computer Science |
| Sujets: | |
| Accès en ligne: | https://peerj.com/articles/cs-3000.pdf |
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