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Using Wearable Activity Trackers to Predict Type 2 Diabetes: Machine Learning–Based Cross-sectional Study of the UK Biobank Accelerometer Cohort
BACKGROUND: Between 2013 and 2015, the UK Biobank collected accelerometer traces from 103,712 volunteers aged between 40 and 69 years using wrist-worn triaxial accelerometers for 1 week. This data set has been used in the past to verify that individuals with chronic diseases exhibit reduced activity...
Autores principales: | Lam, Benjamin, Catt, Michael, Cassidy, Sophie, Bacardit, Jaume, Darke, Philip, Butterfield, Sam, Alshabrawy, Ossama, Trenell, Michael, Missier, Paolo |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8080299/ https://www.ncbi.nlm.nih.gov/pubmed/33739298 http://dx.doi.org/10.2196/23364 |
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