Tuning neural and fuzzy-neural networks for toxicity modeling

P. Mazzatorta, E. Benfenati, C. D. Neagu, G. Gini

Research output: Contribution to journalArticlepeer-review


The need for general reliable models for predicting toxicity has led to the use of artificial intelligence. We applied neural and fuzzy-neural networks with the QSAR approach. We underline how the networks have to be tuned on the data sets generally involved in modeling toxicity. This study was conducted on 562 organic compounds in order to establish models for predictive the acute toxicity in fish.

Original languageEnglish
Pages (from-to)513-518
Number of pages6
JournalJournal of Chemical Information and Computer Sciences
Issue number2
Publication statusPublished - Mar 2003

ASJC Scopus subject areas

  • Chemistry(all)
  • Computational Theory and Mathematics
  • Computer Science Applications
  • Information Systems


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