A comprehensive machine learning-based models for predicting mixture toxicity of azole fungicides toward algae (Auxenochlorella pyrenoidosa)

Quantitative structure–activity relationships (QSARs) have been used to predict mixture toxicity. However, current research faces gaps in achieving accurate predictions of the mixture toxicity of azole fungicides. To address this gap, the application of machine learning (ML) algorithms has emerged a...

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Hlavní autoři:	Li-Tang Qin, Xue-Fang Tian, Jun-Yao Zhang, Yan-Peng Liang, Hong-Hu Zeng, Ling-Yun Mo
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Elsevier 2024-12-01
Edice:	Environment International
Témata:	Azole Fungicides QSARs Machine Learning Algorithms Consensus Model
On-line přístup:	http://www.sciencedirect.com/science/article/pii/S0160412024007487
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

A comprehensive machine learning-based models for predicting mixture toxicity of azole fungicides toward algae (Auxenochlorella pyrenoidosa)

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