Using Machine Learning to Classify Bioactivity for 3486 Per- and Polyfluoroalkyl Substances (PFASs) from the OECD List-Reference-Cited by-同舟云学术

Using Machine Learning to Classify Bioactivity for 3486 Per- and Polyfluoroalkyl Substances (PFASs) from the OECD List

Published:2019-10-29 Issue:23 Volume:53 Page:13970-13980
ISSN:0013-936X
Container-title:Environmental Science & Technology
language:en
Short-container-title:Environ. Sci. Technol.

Author:

Cheng Weixiao¹,Ng Carla A.¹²^ORCID

Affiliation:

1. Department of Civil and Environmental Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States

2. Secondary Appointment, Department of Environmental and Occupational Health, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States

Publisher

American Chemical Society (ACS)

Subject

Environmental Chemistry,General Chemistry

Link

http://pubs.acs.org/doi/pdf/10.1021/acs.est.9b04833

Reference66 articles.

1. Perfluoroalkyl and polyfluoroalkyl substances in the environment: Terminology, classification, and origins

2. Is Indirect Exposure a Significant Contributor to the Burden of Perfluorinated Acids Observed in Humans?

3. Perfluoroalkyl and polyfluoroalkyl substances: current and future perspectives

4. Identification of Novel Fluorochemicals in Aqueous Film-Forming Foams Used by the US Military

5. Determination of fluorotelomer alcohols in selected consumer products and preliminary investigation of their fate in the indoor environment

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