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Construction of environmental risk score beyond standard linear models using machine learning methods: application to metal mixtures, oxidative stress and cardiovascular disease in NHANES

Crossref DOI link: https://doi.org/10.1186/s12940-017-0310-9

Published Online: 2017-09-26

Published Print: 2017-12

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Park, Sung Kyun

Zhao, Zhangchen

Mukherjee, Bhramar
Funding

Funding for this research was provided by:

National Institute of Environmental Health Sciences (R01-ES026578, R01-ES026964, R21-ES020811, P30-ES017885)

National Institute for Occupational Safety and Health (T42-OH008455)

Directorate for Mathematical and Physical Sciences (NSF DMS 1406712)
License Information

Text and Data Mining valid from 2017-09-26

Version of Record valid from 2017-09-26
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Article History

Received: 1 June 2017

Accepted: 21 September 2017

First Online: 26 September 2017

Ethics approval and consent to participate

: NHANES is a publicly available data set and all participants in NHANES provide written informed consent, consistent with approval by the National Center for Health Statistics Institutional Review Board.

: Not Applicable.

: The authors declare that they have no competing interests.

: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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