title: Analysis of the applicability of artificial neural networks for studying blood plasma: determination of magnesium ion concentration as a case study.
abstract: Artificial neural networks are suggested for use in predicting metal ion concentration in human blood plasma. Simulated and available experimental data are used to train the artificial neural network. Particularly, using 850 simulated samples, the network predicted the magnesium-free ion concentration with an average error smaller than 1%. Clinical data recently reported for 20 patients were considered and the artificial neural network predicted the concentration of free magnesium ion with an average error of about 6%. Overall, the approach of using artificial neural networks as an alternative or complementary strategy to deal with the analysis of human blood plasma can be useful for clinical diagnostics, if there is sufficient data to train the artificial neural network.
authors.affiliation: Departamento de Química, Instituto de Ciências Exatas, Universidade Federal de Minas Gerais, Av. Antônio Carlos 6.627, Belo Horizonte, MG, Brazil.
authors.forename: Alexandre
authors.initials: A
authors.lastname: Liparini
authors.forename: Sandra
authors.initials: S
authors.lastname: Carvalho
authors.forename: Jadson C
authors.initials: JC
authors.lastname: Belchior
mesh_terms: D006801:Humans; D006863:Hydrogen-Ion Concentration; D008274:Magnesium / Q000097:blood*; D008875:Middle Aged; D016571:Neural Networks, Computer; D010949:Plasma / Q000737:chemistry*; D011237:Predictive Value of Tests
chemical_list: D008274:Magnesium