Recent Submissions

  • Estimating the real burden of disease under a pandemic situation: the SARS-CoV2 case 

    Fernandez Fontelo, Amanda; Moriña, David; Cabaña Nigro, Ana Alejandra; Arratia Quesada, Argimiro Alejandro; Puig, Pedro (Public Library of Science (PLOS), 2020-12-03)
    Article
    Open Access
    The present paper introduces a new model used to study and analyse the severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) epidemic-reported-data from Spain. This is a Hidden Markov Model whose hidden layer is a ...
  • Leveraging data science for a personalized haemodialysis 

    Hueso, Miguel; Haro Martín, Luis de; Calabria, Jordi; Dal-Re, R; Tebe, C; Gibert, Karina; Cruzado, Josep M; Vellido Alcacena, Alfredo (Karger, 2020-11)
    Article
    Open Access
    The 2019 Science for Dialysis Meeting at Bellvitge University Hospital was devoted to the challenges and opportunities posed by the use of data science to facilitate precision and personalized medicine in nephrology, and ...
  • Helping decision-makers manage resilience under different climate change scenarios: global vs local 

    Nebot Castells, M. Àngela (2021-02-18)
    Article
    Open Access
    The Intergovernmental Panel on Climate Change (IPCC) fifth assessment report states that warming of the climate system is unequivocal and notes that each of the last three decades has been successively warmer at the Earth’s ...
  • Unraveling response to temozolomide in preclinical GL261 glioblastoma with MRI/MRSI using radiomics and signal source extraction 

    Nuñez Vivero, Luis Miguel; Romero Merino, Enrique; Julia Sape, Margarida; Ledesma Carballo, María Jesús; Santos, Andrés; Arus Caraltó, Carles; Candiota Silveira, Ana Paula; Vellido Alcacena, Alfredo (Nature, 2020-11-12)
    Article
    Open Access
    Glioblastoma is the most frequent aggressive primary brain tumor amongst human adults. Its standard treatment involves chemotherapy, for which the drug temozolomide is a common choice. These are heterogeneous and variable ...
  • An e-Learning toolbox based on rule-based fuzzy approaches 

    Nebot Castells, M. Àngela; Múgica Álvarez, Francisco; Castro Espinoza, Félix Agustín (Multidisciplinary Digital Publishing Institute, 2020-09-28)
    Article
    Open Access
    In this paper, an e-Learning toolbox based on a set of fuzzy logic data mining techniques is presented. The toolbox is mainly based on the fuzzy inductive reasoning (FIR) methodology and two of its key extensions: (i) the ...
  • On-the-fly syntheziser programming with fuzzy rule learning 

    Paz Ortiz, Alejandro Iván; Nebot Castells, M. Àngela; Múgica Álvarez, Francisco; Romero Merino, Enrique (2020-08-31)
    Article
    Open Access
    This manuscript explores fuzzy rule learning for sound synthesizer programming within the performative practice known as live coding. In this practice, sound synthesis algorithms are programmed in real time by means of ...
  • On the use of pairwise distance learning for brain signal classification with limited observations 

    Calhas, David; Romero Merino, Enrique; Henriques, Rui (2020-05)
    Article
    Restricted access - publisher's policy
    The increasing access to brain signal data using electroencephalography creates new opportunities to study electrophysiological brain activity and perform ambulatory diagnoses of neurological disorders. This work proposes ...
  • Integral seismic risk assessment through fuzzy models 

    González Cardenas, Rubén; Nebot Castells, M. Àngela; Múgica Álvarez, Francisco (Multidisciplinary Digital Publishing Institute, 2020-04-26)
    Article
    Open Access
    The usage of indicators as constituent parts of composite indices is an extended practice in many fields of knowledge. Even if rigorous statistical analyses are implemented, many of the methodologies follow simple arithmetic ...
  • Male and female politicians on Twitter: A machine learning approach 

    Beltran Jorba, Javier; Gallego Dobón, Aina; Huidobro Torres, Alba; Romero Merino, Enrique; Padró, Lluís (2021-02)
    Article
    Restricted access - publisher's policy
    How does the language of male and female politicians differ when they communicate directly with the public on social media? Do citizens address them differently? We apply Lasso logistic regression models to identify the ...
  • Feature selection for microarray gene expression data using simulated annealing guided by the multivariate joint entropy 

    González Navarro, Félix Fernando; Belanche Muñoz, Luis Antonio (2014-04-01)
    Article
    Open Access
    Microarray classification poses many challenges for data analysis, given that a gene expression data set may consist of dozens of observations with thousands or even tens of thousands of genes. In this context, feature ...
  • Fuzzy heterogeneous neurons for imprecise classification problems 

    Valdés Ramos, Julio José; Belanche Muñoz, Luis Antonio; Alquézar Mancho, René (Wiley, 2000-02)
    Article
    Open Access
    In the classical neuron model, inputs are continuous real-valued quantities. However, in many important domains from the real world, objects are described by a mixture of continuous and discrete variables, usually containing ...
  • Towards a model of input-output behaviour of wastewater treatment plants using soft computing techniques 

    Belanche Muñoz, Luis Antonio; Valdés Ramos, Julio José; Comas Matas, Joaquim; Rodriguez Roda, Ignasi; Poch Espallargas, Manel (Elsevier, 1999-03)
    Article
    Open Access
    Wastewater Treatment Plants (WWTPs) control and prediction under a wide range of operating conditions is an important goal in order to avoid breaking of environmental balance, keeping the system in stable operating conditions ...

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