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Massive online data annotation, crowdsourcing to generate high quality sleep spindle annotations from EEG data
Spindle event detection is a key component in analyzing human sleep. However, detection of these oscillatory patterns by experts is time consuming and costly. Automated detection algorithms are cost efficient and reproducible but require robust datasets to be trained and validated. Using the MODA (M...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7305234/ https://www.ncbi.nlm.nih.gov/pubmed/32561751 http://dx.doi.org/10.1038/s41597-020-0533-4 |