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Automated feature extraction from population wearable device data identified novel loci associated with sleep and circadian rhythms
Wearable devices have been increasingly used in research to provide continuous physical activity monitoring, but how to effectively extract features remains challenging for researchers. To analyze the generated actigraphy data in large-scale population studies, we developed computationally efficient...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Public Library of Science
2020
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7595622/ https://www.ncbi.nlm.nih.gov/pubmed/33075057 http://dx.doi.org/10.1371/journal.pgen.1009089 |