An artificial intelligence-based model for predicting reproductive toxicity of bisphenol analogues mixtures to the rotifer Brachionus calyciflorus-Reference-Cited by-同舟云学术

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An artificial intelligence-based model for predicting reproductive toxicity of bisphenol analogues mixtures to the rotifer Brachionus calyciflorus

Published:2024-06 Issue: Volume:929 Page:172537
ISSN:0048-9697
Container-title:Science of The Total Environment
language:en
Short-container-title:Science of The Total Environment

Author:

Wang Yilin,Fan Juntao,Guo Fen,Yu Songyan,Yan Zhenguang

Funder

Science and Technology Planning Project of Guangdong Province

Ministry of Science and Technology of the People's Republic of China

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference42 articles.

1. In Optuna: A Next-Generation Hyperparameter Optimization Framework, 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD), Anchorage, AK, Aug 04–08, 2019;Akiba,2019

2. Predictive environmental risk assessment of chemical mixtures: a conceptual framework;Backhaus;Environ. Sci. Technol.,2012

3. A review of quantitative structure-activity relationship modelling approaches to predict the toxicity of mixtures. Computational;Belfield;Toxicology,2023

4. Random forests;Breiman;Mach. Learn.,2001

5. Modeling the toxicity of pollutants mixtures for risk assessment: a review;Bures;Environ. Chem. Lett.,2021

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