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Validation of counter propagation neural network models for predictive toxicology according to the OECD principles: a case study

VRACKO M
•
BANDELJ V
•
BARBIERI, PIERLUIGI
altro
WORTH A.
2006
  • journal article

Periodico
SAR AND QSAR IN ENVIRONMENTAL RESEARCH
Abstract
The OECD has proposed five principles for validation of QSAR models used for regulatory purposes. Here we present a case study investigating how these principles can be applied to models based on Kohonen and counter propagation neural networks. The study is based on a counter propagation network model that has been built using toxicity data in fish fathead minnow for 541 compounds. The study demonstrates that most, if not all, of the OECD criteria may be met when modeling using this neural network approach.
DOI
10.1080/10659360600787650
Archivio
http://hdl.handle.net/11368/1690319
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-33745808006
Diritti
metadata only access
Soggetti
  • Predictive Toxicology...

  • Validation of QSAR mo...

  • Counter propagation n...

  • Duluth database

Web of Science© citazioni
35
Data di acquisizione
Mar 28, 2024
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