The use of Artificial Neural Network for lipid and glycaemic profiles quantification through infrared spectroscopy - Hesse, Henrique; Frozza, Rejane; Corbellini, Valeriano; Reuter, Cézane; Burgos, Miria (Anais do Simpósio Brasileiro de Computação Aplicada à Saúde (SBCAS); 2016: Anais do XVI Workshop de Informática MédicaDO - 10.5753/sbcas.2016.9910, 2016)
This paper aims to look at the viability of the use of artificial neural networks to solve nonlinear correlations between infrared spectra and biochemical quantification tests, to build a computational system to predict the levels of glycaemic and lipid profiles using infrared spectroscopy. The studies of one of the parameters was modelled and showed signs of viability to quantify all parameters with the suggested methodology. Therefore, more complex and larger data sets are going to be tested with this technique.