Pharmacokinetic applications of fuzzy structure identification and reasoning

Official URL: http://dx.doi.org/10.1016/j.ins.2004.03.005

The aim of this paper is to introduce the algorithm proposed in [8] and some further modifications. Its applications presented in [8, 9] is reviewed as a full collection of its use in pharmacokinetic analysis. First a recently developed fuzzy system modeling algorithm and approximate reasoning tool are introduced along with the modifications. Later the performance of the proposed algorithm is tested in two different data sets and compared with some well-known algorithms from the literature. In the comparison, individualized pharmacokinetic data,( i.e., alprazolam data) and population pharmacokinetic data, (i.e, lithium data) are used. The comparisons demonstrate that the proposed algorithm can be successfully applied in pharmacokinetic modeling.