Digital envirotyping: quantifying environmental determinants of health and behavior
Digital phenotyping efforts have used wearable devices to connect a rich array of physiologic data to health outcomes or behaviors of interest. The environmental context surrounding these phenomena has received less attention, yet is critically needed to understand their antecedents and deliver cont...
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Nature Portfolio
2020
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oai:doaj.org-article:5475b55eec834a78a3f3255afc243b382021-12-02T11:36:25ZDigital envirotyping: quantifying environmental determinants of health and behavior10.1038/s41746-020-0245-32398-6352https://doaj.org/article/5475b55eec834a78a3f3255afc243b382020-03-01T00:00:00Zhttps://doi.org/10.1038/s41746-020-0245-3https://doaj.org/toc/2398-6352Digital phenotyping efforts have used wearable devices to connect a rich array of physiologic data to health outcomes or behaviors of interest. The environmental context surrounding these phenomena has received less attention, yet is critically needed to understand their antecedents and deliver context-appropriate interventions. The coupling of improved smart eyewear with deep learning represents a technological turning point, one that calls for more comprehensive, ambitious study of environments and health.Matthew M. EngelhardJason A. OliverF. Joseph McClernonNature PortfolioarticleComputer applications to medicine. Medical informaticsR858-859.7ENnpj Digital Medicine, Vol 3, Iss 1, Pp 1-3 (2020) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
Computer applications to medicine. Medical informatics R858-859.7 |
| spellingShingle |
Computer applications to medicine. Medical informatics R858-859.7 Matthew M. Engelhard Jason A. Oliver F. Joseph McClernon Digital envirotyping: quantifying environmental determinants of health and behavior |
| description |
Digital phenotyping efforts have used wearable devices to connect a rich array of physiologic data to health outcomes or behaviors of interest. The environmental context surrounding these phenomena has received less attention, yet is critically needed to understand their antecedents and deliver context-appropriate interventions. The coupling of improved smart eyewear with deep learning represents a technological turning point, one that calls for more comprehensive, ambitious study of environments and health. |
| format |
article |
| author |
Matthew M. Engelhard Jason A. Oliver F. Joseph McClernon |
| author_facet |
Matthew M. Engelhard Jason A. Oliver F. Joseph McClernon |
| author_sort |
Matthew M. Engelhard |
| title |
Digital envirotyping: quantifying environmental determinants of health and behavior |
| title_short |
Digital envirotyping: quantifying environmental determinants of health and behavior |
| title_full |
Digital envirotyping: quantifying environmental determinants of health and behavior |
| title_fullStr |
Digital envirotyping: quantifying environmental determinants of health and behavior |
| title_full_unstemmed |
Digital envirotyping: quantifying environmental determinants of health and behavior |
| title_sort |
digital envirotyping: quantifying environmental determinants of health and behavior |
| publisher |
Nature Portfolio |
| publishDate |
2020 |
| url |
https://doaj.org/article/5475b55eec834a78a3f3255afc243b38 |
| work_keys_str_mv |
AT matthewmengelhard digitalenvirotypingquantifyingenvironmentaldeterminantsofhealthandbehavior AT jasonaoliver digitalenvirotypingquantifyingenvironmentaldeterminantsofhealthandbehavior AT fjosephmcclernon digitalenvirotypingquantifyingenvironmentaldeterminantsofhealthandbehavior |
| _version_ |
1718395759088369664 |