Machine Learning for Evaluating the Cytotoxicity of Mixtures of Nano-TiO2 and Heavy Metals: QSAR Model Apply Random Forest Algorithm after Clustering Analysis

With the development and application of nanomaterials, their impact on the environment and organisms has attracted attention. As a common nanomaterial, nano-titanium dioxide (nano-TiO2) has adsorption properties to heavy metals in the environment. Quantitative structure-activity relationship (QSAR)...

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Bibliographic Details
Published in:	Molecules (Basel, Switzerland) Vol. 27; no. 18; p. 6125
Main Authors:	Sang, Leqi, Wang, Yunlin, Zong, Cheng, Wang, Pengfei, Zhang, Huazhong, Guo, Dan, Yuan, Beilei, Pan, Yong
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 19.09.2022 MDPI
Subjects:	Accuracy AdaBoost Algorithms Cluster analysis Clustering Composite materials Cytotoxicity Decision trees Machine learning Metal oxides Metals mixture Nanomaterials Nanoparticles Particle size Pollutants QSAR
ISSN:	1420-3049, 1420-3049
Online Access:	Get full text
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