Automated feature extraction from population wearable device data identified novel loci associated w...
Automated feature extraction from population wearable device data identified novel loci associated with sleep and circadian rhythms
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United States: Public Library of Science
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Language
English
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Publisher
United States: Public Library of Science
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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 methods to derive sleep and activity features thr...
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Full title
Automated feature extraction from population wearable device data identified novel loci associated with sleep and circadian rhythms
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TN_cdi_plos_journals_2460111109
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_2460111109
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ISSN
1553-7404,1553-7390
E-ISSN
1553-7404
DOI
10.1371/journal.pgen.1009089
