• Algoritmos de aprendizaje neurocomputacionales para su implementación hardware 

      Ortega Zamorano, Francisco (Servicio de Publicaciones y Divulgación Científica, 2015)
      Las redes de neuronas artificiales son un paradigma de aprendizaje y procesamiento automático inspirado en el funcionamiento del sistema nervioso, se emplean en toda tipo de aplicaciones, con lo que van apareciendo nuevas ...
    • Análisis de citoquinas en pacientes adictos a la cocaína 

      Maza Quiroga, Rosa María (2018-03-05)
      La adicción a la cocaína es un problema de salud creciente, siendo España el país de la Unión Europea donde se produce el mayor consumo de esta sustancia. La adicción conlleva el desarrollo de comorbilidad psiqui atrica, ...
    • Classification of high dimensional data using LASSO ensembles 

      Urda, Daniel; Franco, Leonardo; Jerez, J.M.
      The estimation of multivariable predictors with good performance in high dimensional settings is a crucial task in biomedical contexts. Usually, solutions based on the application of a single machine ...
    • Deep Learning to Analyze RNA-Seq Gene Expression Data 

      Urda, Daniel; Montes-Torres, Julio; Moreno, Fernando; Franco, Leonardo; Jerez-Aragonés, José Manuel (Springer, 2017)
      Deep learning models are currently being applied in several areas with great success. However, their application for the analysis of high-throughput sequencing data remains a challenge for the research community due to ...
    • Diseño de sistemas neurocomputacionales en el ámbito de la Biomedicina 

      Urda Muñoz, Daniel (Servicio de Publicaciones y Divulgación Científica, 2014)
      El área de la biomedicina es un área extensa en el que las entidades públicas de cada país han invertido y continúan invirtiendo en investigación una gran cantidad de financiación a través de proyectos nacionales, europeos ...
    • Machine learning models to search relevant genetic signatures in clinical context 

      Urda, Daniel; Luque-Baena, Rafael; Franco, Leonardo; Sánchez-Maroño, Noelia; Jerez-Aragonés, José Manuel (2017-06-26)
      Clinicians are interested in the estimation of robust and relevant genetic signatures from gene sequencing data. Many machine learning approaches have been proposed trying to address well-known issues of this complex ...
    • SIMNET: simulation-based exercises for computer net-work curriculum through gamification and augmented reality 

      Fraga, Álvaro Luis; Gramajo, María Guadalupe; Trejo, Federico; García, Selena; Juárez, Gustavo; [et al.] (University of Applied Sciences, Dusseldorf, Alemania., 2018)
      Gamification and Augmented Reality techniques, in recent years, have tackled many subjects and environments. Its implementation can, in particular, strengthen teaching and learning processes in schools and universities. ...
    • Solving Scheduling Problems with Genetic Algorithms using a Priority Encoding Scheme 

      Subirats, J.L.; Mesa, Héctor; Ortega-Zamorano, Francisco; Juárez, G.E.; Jerez-Aragonés, José Manuel; [et al.] (2017-06-26)
      Scheduling problems are very hard computational tasks with several applications in multitude of domains. In this work we solve a practical problem motivated by a real industry situation, in which we apply a genetic algorithm ...
    • A transfer-learning approach to feature extraction from cancer transcriptomes with deep autoencoders 

      López-García, Guillermo; Jerez, José M; Franco, Leonardo; Veredas-Navarro, Francisco Javier (2019-06-18)
      The diagnosis and prognosis of cancer are among the more challenging tasks that oncology medicine deals with. With the main aim of fitting the more appropriate treatments, current personalized medicine focuses on using ...