Deep longitudinal phenotyping of wearable sensor data reveals independent markers of longevity, stress, and resilience

Biological age acceleration (BAA) models based on blood tests or DNA methylation emerge as a de facto standard for quantitative characterizations of the aging process. We demonstrate that deep neural networks trained to predict morbidity risk from wearable sensor data can provide a high-quality and...

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Detalles Bibliográficos
Autores principales: Pyrkov, Timothy V., Sokolov, Ilya S., Fedichev, Peter O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2021
Materias:
Research Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8034931/
https://www.ncbi.nlm.nih.gov/pubmed/33735108
http://dx.doi.org/10.18632/aging.202816

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8034931/
https://www.ncbi.nlm.nih.gov/pubmed/33735108
http://dx.doi.org/10.18632/aging.202816

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