| Autor: |
Mistry, Pritesh, Neagu, Daniel, Sanchez-Ruiz, Antonio, Trundle, Paul R., Vessey, Jonathan D., Gosling, John Paul |
| Zdroj: |
Toxicology Research; 2017, Vol. 6 Issue: 1 p42-53, 12p |
| Abstrakt: |
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. |
| Databáze: |
Supplemental Index |
| Externí odkaz: |
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