Ontology highlight
ABSTRACT:
SUBMITTER: Mistry P
PROVIDER: S-EPMC5310521 | biostudies-literature | 2017 Jan
REPOSITORIES: biostudies-literature
Mistry Pritesh P Neagu Daniel D Sanchez-Ruiz Antonio A Trundle Paul R PR Vessey Jonathan D JD Gosling John Paul JP
Toxicology research 20161031 1
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. ...[more]