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Araya-Diaz, P., Ruz, G. A., & Palomino, H. M. (2013). Discovering Craniofacial Patterns Using Multivariate Cephalometric Data for Treatment Decision Making in Orthodontics. Int. J. Morphol., 31(3), 1109–1115.
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Goles, E., & Ruz, G. A. (2015). Dynamics of neural networks over undirected graphs. Neural Netw., 63, 156–169.
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Goles, E., Montalva, M., & Ruz, G. A. (2013). Deconstruction and Dynamical Robustness of Regulatory Networks: Application to the Yeast Cell Cycle Networks. Bull. Math. Biol., 75(6), 939–966.
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Henriquez, P. A., & Ruz, G. A. (2017). Extreme learning machine with a deterministic assignment of hidden weights in two parallel layers. Neurocomputing, 226, 109–116.
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Mascareno, A., Goles, E., & Ruz, G. A. (2016). Crisis in complex social systems: A social theory view illustrated with the chilean case. Complexity, 21(S2), 13–23.
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Pham, D. T., & Ruz, G. A. (2009). Unsupervised training of Bayesian networks for data clustering. Proc. R. Soc. A-Math. Phys. Eng. Sci., 465(2109), 2927–2948.
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Rodríguez-Valdecantos, G., Manzano, M., Sánchez, R., Urbina, F., Hengst, M. B., Lardies, M. A., et al. (2017). Early successional patterns of bacterial communities in soil microcosms reveal changes in bacterial community composition and network architecture, depending on the successional condition. Applied Soil Ecology, 120, 44–54.
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Ruz, G. A. (2016). Improving the performance of inductive learning classifiers through the presentation order of the training patterns. Expert Syst. Appl., 58, 1–9.
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Ruz, G. A., & Goles, E. (2013). Learning gene regulatory networks using the bees algorithm. Neural Comput. Appl., 22(1), 63–70.
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Ruz, G. A., & Pham, D. T. (2012). NBSOM: The naive Bayes self-organizing map. Neural Comput. Appl., 21(6), 1319–1330.
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Ruz, G. A., Goles, E., Montalva, M., & Fogel, G. B. (2014). Dynamical and topological robustness of the mammalian cell cycle network: A reverse engineering approach. Biosystems, 115, 23–32.
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Ruz, G. A., Timmermann, T., Barrera, J., & Goles, E. (2014). Neutral space analysis for a Boolean network model of the fission yeast cell cycle network. Biol. Res., 47, 12 pp.
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Ruz, G. A., Varas, S., & Villena, M. (2013). Policy making for broadband adoption and usage in Chile through machine learning. Expert Syst. Appl., 40(17), 6728–6734.
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Valle, M. A., & Ruz, G. A. (2015). Turnover Prediction In A Call Center: Behavioral Evidence Of Loss Aversion Using Random Forest And Naive Bayes Algorithms. Appl. Artif. Intell., 29(9), 923–942.
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Valle, M. A., Ruz, G. A., & Masías, V. H. (2017). Using self-organizing maps to model turnover of sales agents in a call center. Appl. Soft Comput., to appear.
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Valle, M. A., Ruz, G. A., & Varas, S. (2015). A survival model based on met expectations Application to employee turnover in a call center. Acad.-Rev. Latinoam. Adm., 28(2), 177–194.
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Valle, M. A., Ruz, G. A., & Varas, S. (2015). Explaining job satisfaction and intentions to quit from a value-risk perspective. Acad.-Rev. Latinoam. Adm., 28(4), 523–540.
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Valle, M. A., Varas, S., & Ruz, G. A. (2012). Job performance prediction in a call center using a naive Bayes classifier. Expert Syst. Appl., 39(11), 9939–9945.
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Zuniga, A., Donoso, R. A., Ruiz, D., Ruz, G. A., & Gonzalez, B. (2017). Quorum-Sensing Systems in the Plant Growth-Promoting Bacterium Paraburkholderia phytofirmans PsJN Exhibit Cross-Regulation and Are Involved in Biofilm Formation. Mol. Plant-Microbe Interact., 30(7), 557–565.
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