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Performance comparison of machine learning techniques in sleep scoring based on wavelet features and neighboring component analysis
INTRODUCTION: Sleep scoring is an important step in the treatment of sleep disorders. Manual annotation of sleep stages is time-consuming and experience-relevant and, therefore, needs to be done using machine learning techniques. METHODS: Sleep-EDF polysomnography was used in this study as a dataset...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
PeerJ Inc.
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6064207/ https://www.ncbi.nlm.nih.gov/pubmed/30065866 http://dx.doi.org/10.7717/peerj.5247 |