Automated machine learning in nanotoxicity assessment: A comparative study of predictive model performance-Reference-Cited by-同舟云学术

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Automated machine learning in nanotoxicity assessment: A comparative study of predictive model performance

Published:2024-12 Issue: Volume:25 Page:9-19
ISSN:2001-0370
Container-title:Computational and Structural Biotechnology Journal
language:en
Short-container-title:Computational and Structural Biotechnology Journal

Author:

Xiao Xiao,Trinh Tung X.,Gerelkhuu Zayakhuu^ORCID,Ha Eunyong^ORCID,Yoon Tae Hyun

Publisher

Elsevier BV

Reference46 articles.

1. Nanomaterials in cosmetics: recent updates;Fytianos;Nanomater,2020

2. Photocatalytic and biological applications of Ag and Au doped ZnO nanomaterial synthesized by combustion;Pathak;Vacuum,2018

3. Noble metal nanoparticles for biosensing applications;Doria;Sensors,2012

4. Single small molecule-assembled nanoparticles mediate efficient oral drug delivery;Yang;Nano Res,2019

5. Ongoing inflammation enhances the toxicity of engineered nanomaterials: application of an in vitro co-culture model of the healthy and inflamed intestine;Kämpfer;Toxicol Vitr,2020

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. In silico assessment of nanoparticle toxicity powered by the Enalos Cloud Platform: Integrating automated machine learning and synthetic data for enhanced nanosafety evaluation;Computational and Structural Biotechnology Journal;2024-12

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