The prediction of methylmercury elimination half-life in humans using animal data: a neural network/rough sets analysis.

@article{Hashemi2003ThePO,
  title={The prediction of methylmercury elimination half-life in humans using animal data: a neural network/rough sets analysis.},
  author={Ray R. Hashemi and John Fariselli Young},
  journal={Journal of toxicology and environmental health. Part A},
  year={2003},
  volume={66 23},
  pages={2227-52}
}
Artificial neural networks and Rough Sets methodology have been utilized to predict human pharmacokinetic elimination half-life data based on animal data training sets. Methylmercury (Hg) pharmacokinetic data was obtained from 37 literature references, which provided data on species, gender, age, weight, route of administration, dose, dose frequency, and elimination half-life based on either whole-body Hg analysis or blood Hg analysis. Data were categorized into various formats for analysis… CONTINUE READING