Predicting In Vitro Neurotoxicity Induced by Nanoparticles Using Machine Learning.

ABSTRACT: The practice of non-testing approaches in nanoparticles hazard assessment is necessary to identify and classify potential risks in a cost effective and timely manner. Machine learning techniques have been applied in the field of nanotoxicology with encouraging results. A neurotoxicity classification model for diverse nanoparticles is presented in this study. A data set created from multiple literature sources consisting of nanoparticles physicochemical properties, exposure conditions and in vitro characteristics is compiled to predict cell viability. Pre-processing techniques were applied such as normalization methods and two supervised instance methods, a synthetic minority over-sampling technique to address biased predictions and production of subsamples via bootstrapping. The classifica

SUBMITTER: Furxhi I 

PROVIDER: S-EPMC7432486 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature