Machine Learning (ML) and Toxicity Studies
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-16-8881-2_21
Reference27 articles.
1. Ai H, Wu X, Zhang L et al (2019) QSAR modelling study of the bioconcentration factor and toxicity of organic compounds to aquatic organisms using machine learning and ensemble methods. Ecotoxicol Environ Saf 179:71–78
2. Attene-Ramos MS, Miller N, Huang R et al (2013) The Tox21 robotic platform for the assessment of environmental chemicals--from vision to reality. Drug Discov Today 18(15–16):716–723
3. Basile AO, Yahi A, Tatonetti NP (2019) Artificial intelligence for drug toxicity and safety trends. Pharmacol Sci 40(9):624–635
4. Cao L, Zhu P, Zhao Y, Zhao J (2018) Using machine learning and quantum chemistry descriptors to predict the toxicity of ionic liquids. J Hazard Mater 352:17–26
5. Cipullo S, Snapir B, Prpich G, Campo P, Coulon F (2019) Prediction of bioavailability and toxicity of complex chemical mixtures through machine learning models. Chemosphere 215:388–395
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