Abstract
This paper presents the development of a nutritional system using radial basis neural networks, that is able to provide a clear and simple prediction problems of obesity in children up to twelve years, based on your eating habits during the day. For the development of this project has taken into account various factors that are vital for the proper development of infants. A prediction system can offer a solution to several factors, which are not easily determined by conventional means. The results obtained from a sample of 186 children at primary level to obtain characteristic behaviors of the developed system are detailed in this paper. Currently, in view of the serious problem of overweight and obesity worldwide, primary schools, because of their characteristics of having a captive population and vulnerable to the benefits of education, have been identified as a suitable area for intervention studies with components to prevent this problem, considering the energy balance and the ecological models. Although there are numerous studies, at present there is no strategy that could be applied universally in schools.
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Medina-Santiago, A. et al. (2018). Neural Network Backpropagation with Applications into Nutrition. In: Chen, YW., Tanaka, S., Howlett, R., Jain, L. (eds) Innovation in Medicine and Healthcare 2017. KES-InMed 2018 2017. Smart Innovation, Systems and Technologies, vol 71. Springer, Cham. https://doi.org/10.1007/978-3-319-59397-5_6
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DOI: https://doi.org/10.1007/978-3-319-59397-5_6
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