Browsing by Subject "Machine learning"

Now showing items 21-28 of 28

    • Predicting EHL film thickness parameters by machine learning approaches 
      Marian, Max; Mursak, Jonas; Bartz, Marcel; Profito, Francisco J.; Rosenkranz, Andreas; Wartzack, Sandro (Springer, 2022)
      Non-dimensional similarity groups and analytically solvable proximity equations can be used to estimate integral fluid film parameters of elastohydrodynamically lubricated (EHL) contacts. In this contribution, we demonstrate ...
    • Predicting nationwide obesity from food sales using machine learning 
      Dunstan, Jocelyn; Aguirre Jerez, Marcela; Bastías García, Magdalena; Nau, Claudia; Glass, Thomas A.; Tobar, Felipe (SAGE, 2020)
      The obesity epidemic progresses everywhere across the globe, and implementing frequent nationwide surveys to measure the percentage of obese population is costly. Conversely, country-level food sales information can be ...
    • Predicting stroke risk with an interpretable classifier 
      Peñafiel, Sergio; Baloian Tataryan, Nelson; Sanson, Horacio; Pino Urtubia, José (IEEE-Inst Electrical Electronics Engineers, 2021)
      Predicting an individual's risk of getting a stroke has been a research subject for many authors worldwide since it is a frequent illness and there is strong evidence that early awareness of having that risk can be bene ...
    • Setting up standards: A methodological proposal for pediatric Triage machine learning model construction ... 
      Wolff Rojas, Patricio; Ríos, Sebastián A.; Graña, Manuel (Elsevier Ltd, 2019)
      © 2019 Elsevier LtdTriage is a critical process in hospital emergency departments (ED). Specifically, we consider how to achieve fast and accurate patient Triage in the ED of a pediatric hospital. The goal of this paper ...
    • The use of artificial intelligence in tribology—a perspective 
      Rosenkranz, Andreas; Marian, Max; Profito, Francisco J.; Aragón, Nathan; Shah, Raj (MDPI, 2021)
      Artificial intelligence and, in particular, machine learning methods have gained notable attention in the tribological community due to their ability to predict tribologically relevant parameters such as, for instance, the ...
    • Triage prediction in pediatric patients with respiratory problems 
      Garmendia, Asier; Rios, Sebastian A.; Lopez-Guede, Jose M.; Graña, Manuel (Elsevier B.V., 2019)
      © 2017 Elsevier B.V. Respiratory diseases have an increasing prevalence in the large urban concentration of the world, due to the apparently unstoppable increase of air pollution from a diversity of sources. Children are ...
    • Unsupervised learning of structure in spectroscopic cubes 
      Araya, M.; Mendoza, M.; Solar, M.; Mardones, D.; Bayo, A. (Elsevier B.V., 2018)
      © 2018 Elsevier B.V. We consider the problem of analyzing the structure of spectroscopic cubes using unsupervised machine learning techniques. We propose representing the target's signal as a homogeneous set of volumes ...
    • Using psychophysiological sensors to assess mental workload during web browsing 
      Jiménez Molina, Ángel; Retamal, Cristian; Lira, Hernan (MDPI, 2018)
      Knowledge of the mental workload induced by a Web page is essential for improving users' browsing experience. However, continuously assessing the mental workload during a browsing task is challenging. To address this issue, ...