Application of Artificial Neural Networks for the Voltammetry Quantification of Diclofenac Using a Carbon-Paste Electrode with Carbon Nanotubes

In this work, Artificial Neural Networks (ANN) are used for the electrochemical quantification of diclofenac in presence of naproxen and paracetamol as main interferences. A carbon paste multi-walled nanotubes electrode is used to achieve the analytical signal by means of differential pulse voltamme...

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Bibliographic Details
Published in:ECS transactions 2017-04, Vol.76 (1), p.19-27
Main Authors: Aguilar-Lira, Guadalupe Yoselin, Gutiérrez Salgado, Juan Manuel, Rojas-Hernández, Alberto, Rodríguez-Ávila, Jose Antonio, Páez-Hernández, María Elena, Álvarez-Romero, Giaan Arturo
Format: Article
Language:English
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Summary:In this work, Artificial Neural Networks (ANN) are used for the electrochemical quantification of diclofenac in presence of naproxen and paracetamol as main interferences. A carbon paste multi-walled nanotubes electrode is used to achieve the analytical signal by means of differential pulse voltammetry. The architecture of the mathematical model is based on a multilayer perceptron network (MLP) and a bayesian training algorithm. With the trained MLP, r2 values of 0.991 are obtained when testing data for the simultaneous quantification of the three drugs.
ISSN:1938-5862
1938-6737
1938-6737
1938-5862
DOI:10.1149/07601.0019ecst