Two-Stage Machine Learning-Based Approach to Predict Points of Departure for Human Noncancer and Developmental/Reproductive Effects-Reference-Cited by-同舟云学术

Two-Stage Machine Learning-Based Approach to Predict Points of Departure for Human Noncancer and Developmental/Reproductive Effects

Published:2024-05-02 Issue:35 Volume:58 Page:15638-15649
ISSN:0013-936X
Container-title:Environmental Science & Technology
language:en
Short-container-title:Environ. Sci. Technol.

Author:

Kvasnicka Jacob¹^ORCID,Aurisano Nicolò²^ORCID,von Borries Kerstin²^ORCID,Lu En-Hsuan¹,Fantke Peter²^ORCID,Jolliet Olivier²,Wright Fred A.³,Chiu Weihsueh A.¹^ORCID

Affiliation:

1. Department of Veterinary Physiology and Pharmacology, Interdisciplinary Faculty of Toxicology, Texas A&M University, College Station, Texas 77843, United States

2. Quantitative Sustainability Assessment, Department of Environmental and Resource Engineering, Technical University of Denmark, Bygningstorvet 115, 2800 Kgs. Lyngby, Denmark

3. Departments of Statistics and Biological Sciences and Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina 27695, United States

Funder

National Institute of Environmental Health Sciences

Stiftelsen f?r Milj?strategisk Forskning

Horizon 2020 Framework Programme

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.est.4c00172

Reference42 articles.

1. United States Environmental Protection Agency (EPA). U.S. EPA System of Registries Terms & Acronyms; https://sor.epa.gov/sor_internet/registry/termreg/searchandretrieve/termsandacronyms/search.do (accessed 2023–12–01).

2. Life cycle based alternatives assessment (LCAA) for chemical substitution

3. Exposure and toxicity characterization of chemical emissions and chemicals in products: global recommendations and implementation in USEtox

4. Conditional Toxicity Value (CTV) Predictor: An In Silico Approach for Generating Quantitative Risk Estimates for Chemicals

5. Toward a Global Understanding of Chemical Pollution: A First Comprehensive Analysis of National and Regional Chemical Inventories