Listar por autor "Gestal, M."

Mostrando ítems 21-34 de 34

    • Machine Learning-Based Radon Monitoring System 

      Valcarce, Diego; Alvarellos, Alberto; Rabuñal, Juan R.; Dorado, Julián; Gestal, M. (MDPI, 2022)
      [Abstract] Radon (Rn) is a biological threat to cells due to its radioactivity. It is capable of penetrating the human body and damaging cellular DNA, causing mutations and interfering with cellular dynamics. Human exposure ...

    • Markov Mean Properties for Cell Death-Related Protein Classification 

      Fernández-Lozano, Carlos; Gestal, M.; González-Díaz, Humberto; Dorado, Julián; Pazos, A.; Munteanu, Cristian-Robert (Elsevier, 2014-01-31)
      [Abstract] The cell death (CD) is a dynamic biological function involved in physiological and pathological processes. Due to the complexity of CD, there is a demand for fast theoretical methods that can help to find new ...

    • Mejora continua de la calidad de la docencia a partir del análisis de los resultados de evaluación 

      Gestal, M.; Fernán, Carlos; Munteanu, Cristian-Robert; Rabuñal, Juan R.; Dorado, Julián (Asociación de Enseñantes Universitarios de la Informática (AENUI), 2018)
      [Resumen] El objetivo de cualquier docente debería ser la mejora continua en sus materias. En este trabajo se muestra una aproximación para adecuar las enseñanzas a aquellos aspectos más necesarios dentro de una materia. ...

    • Net-Net AutoML Selection of Artificial Neural Network Topology for Brain Connectome Prediction 

      Barreiro, Enrique; Munteanu, Cristian-Robert; Gestal, M.; Rabuñal, Juan R.; Pazos, A.; González-Díaz, Humberto; Dorado, Julián (MDPI, 2020-02-14)
      [Abstract] Brain Connectome Networks (BCNs) are defined by brain cortex regions (nodes) interacting with others by electrophysiological co-activation (edges). The experimental prediction of new interactions in BCNs ...

    • Obtendo información útil para a mellora dunha materia a partir dos resultados dos exames de resposta múltiple 

      Gestal, M.; Munteanu, Cristian-Robert; Rabuñal, Juan R.; Dorado, Julián (Universidade da Coruña, Cufie, 2019)
      [Resumo] Os procesos de avaliación, deben aplicarse ós docentes e mesmo á materia en si, non só ós alumnos. Con esta finalidade formúlase unha análise dos resultados acadados polo alumnado durante a proba de avaliación ...

    • Predicting Inflow Flow in Hydraulic Dams Using Artificial Neural Networks 

      Fernández Sáchez, Alberto; Rabuñal, Juan R.; Cebrián Rivero, Daniel; Pazos, A.; Gestal, M.; Cea, Luis (Universidade da Coruña, Servizo de Publicacións, 2023)
      [Abstract] Accurate prediction of inflow in dams plays a crucial role in water resource management Kim et al. (2019); Vargas-Garay et al. (2018); Zhong et al. (2018) and risk mitigation Costabile et al. (2020); Rabuñal et ...

    • Prediction of Anti-Glioblastoma Drug-Decorated Nanoparticle Delivery Systems Using Molecular Descriptors and Machine Learning 

      Munteanu, Cristian-Robert; Gutiérrez-Asorey, Pablo; Blanes-Rodríguez, Manuel; Hidalgo-Delgado, Ismael; Blanco Liverio, María de Jesús; Galdo, Brais; Porto-Pazos, Ana B.; Gestal, M.; Arrasate, Sonia; González-Díaz, Humberto (MDPI, 2021)
      [Abstract] The theoretical prediction of drug-decorated nanoparticles (DDNPs) has become a very important task in medical applications. For the current paper, Perturbation Theory Machine Learning (PTML) models were built ...

    • Prediction of Antimalarial Drug-Decorated Nanoparticle Delivery Systems with Random Forest Models 

      Urista, Diana V.; Carrué, Diego B.; Otero, Iago; Arrasate, Sonia; Quevedo‐Tumailli, Viviana F.; Gestal, M.; González-Díaz, Humberto; Munteanu, Cristian-Robert (MDPI, 2020-07)
      [Abstract]: Drug-decorated nanoparticles (DDNPs) have important medical applications. The current work combined Perturbation Theory with Machine Learning and Information Fusion (PTMLIF). Thus, PTMLIF models were proposed ...

    • Rudeva: una herramienta para la implantación de rúbricas de evaluación 

      Carballa, Roberto; Gestal, M.; Munteanu, Cristian-Robert; Rabuñal, Juan R.; Dorado, Julián (Universidade da Coruña, Cufie, 2020)
      [Resumen]: En el proceso educativo, uno de los procesos más importantes en el proceso educativo y, a la vez más costosos en cuanto al tiempo dedicado es el relativo a la evaluación (de la Garza, 2004). Sobre todo cuando ...

    • Seguridad electrónica en la gestión de la información 

      Gestal, M.; Pérez, José Luís (Universidade da Coruña, 2011)

    • Special Issue on Applied Artificial Neural Networks 

      Gestal, M. (Multidisciplinary Digital Publishing Institute (MDPI), 2022)
      [Abstract]: Over the years there have been many attempts to understand, and subsequently imitate, the way that humans try to solve problems, so it can help to artificially achieve the same kind of intelligent behavior. ...

    • Texture Analysis in Gel Electrophoresis Images Using an Integrative Kernel-Based Approach 

      Fernández-Lozano, Carlos; Seoane, José A.; Gestal, M.; Gaunt, Tom R.; Dorado, Julián; Pazos, A.; Campbell, Colin (Nature, 2016-01-13)
      [Abstract] Texture information could be used in proteomics to improve the quality of the image analysis of proteins separated on a gel. In order to evaluate the best technique to identify relevant textures, we use several ...

    • Using Genetic Algorithms for Automatic Recurrent ANN Development: an Application to EEG Signal Classification 

      Rivero, Daniel; Aguiar-Pulido, Vanessa; Fernández-Blanco, Enrique; Gestal, M. (Inderscience, 2013)
      [Abstract] ANNs are one of the most successful learning systems. For this reason, many techniques have been published that allow the obtaining of feed-forward networks. However, fe w ...

    • Using Genetic Algorithms to Improve Support Vector Regression in the Analysis of Atomic Spectra of Lubricant Oils 

      Fernández-Lozano, Carlos; Cedrón, Francisco; Rivero, Daniel; Dorado, Julián; Andrade-Garda, José Manuel; Pazos, A.; Gestal, M. (Emerald, 2016-06)
      [Abstract] Purpose – The purpose of this paper is to assess the quality of commercial lubricant oils. A spectroscopic method was used in combination with multivariate regression techniques (ordinary multivariate ...