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Predicting Neurotoxicity of Solvents by haw is a document available to read on EtoBox.

This document describes a study that developed nonlinear qualitative and quantitative structure-toxicity relationship (QSTR) models to predict the acute neurotoxicity of organic solvents using probabilistic neural network (PNN) and generalized regression neural network (GRNN) modeling approaches. The models were able to reliably classify solvents as neurotoxic or non-neurotoxic and predict the endpoint neurotoxicities of diverse organic solvents with high accuracy, demonstrating the potential of these QSTR

Author

haw

Language

EN