Prediction of the effect of formulation on the toxicity of chemicals.
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ABSTRACT: Two approaches for the prediction of which of two vehicles will result in lower toxicity for anticancer agents are presented. Machine-learning models are developed using decision tree, random forest and partial least squares methodologies and statistical evidence is presented to demonstrate that they represent valid models. Separately, a clustering method is presented that allows the ordering of vehicles by the toxicity they show for chemically-related compounds.
SUBMITTER: Mistry P
PROVIDER: S-EPMC5310521 | biostudies-literature |
REPOSITORIES: biostudies-literature
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