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Project: Artificial intelligence applied for the chemometrical recognition of drugs of abuse based on (gas chromatography-) Fourier transform infrared and related structural and toxicological data sets.

project duration
11-DEC-00 – 11-DEC-03
abstract
This project aims to use artificial intelligence in the domain of analytical toxicology. We want to model non-homogenous data sets (different drug classes, FTIR and MS data) through a combination of different chemometric techniques. Such systems should allow the correct classification of unknowns (e.g. new designer drugs) as well as provide objective information concerning the activity, toxicity (structure-activity relationships) through the incorporated structural and toxicological databanks.