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A RUSBoosted tree method for k-complex detection using tunable Q-factor wavelet transform and multi-domain feature extraction
BACKGROUND: K-complex detection traditionally relied on expert clinicians, which is time-consuming and onerous. Various automatic k-complex detection-based machine learning methods are presented. However, these methods always suffered from imbalanced datasets, which impede the subsequent processing...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10043251/ https://www.ncbi.nlm.nih.gov/pubmed/36998730 http://dx.doi.org/10.3389/fnins.2023.1108059 |