Exploració per autor "Vellido Alcacena, Alfredo"
Ara es mostren els items 109-128 de 129
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Seeing is believing: the importance of visualization in real-world machine learning applications
Vellido Alcacena, Alfredo; Martín, José David; Rossi, Fabrice; Lisboa, Paulo J.G. (2011)
Text en actes de congrés
Accés obertThe increasing availability of data sets with a huge amount of information, coded in many diff erent features, justifi es the research on new methods of knowledge extraction: the great challenge is the translation of the ... -
Sepsis mortality prediction with the Quotient Basis Kernel
Ribas Ripoll, Vicent; Vellido Alcacena, Alfredo; Romero Merino, Enrique; Ruiz Rodríguez, Juan Carlos (2014-05)
Article
Accés restringit per política de l'editorialObjective: This paper presents an algorithm to assess the risk of death in patients with sepsis. Sepsis is a common clinical syndrome in the intensive care unit (ICU) that can lead to severe sepsis, a severe state of septic ... -
Societal issues concerning the application of artificial intelligence in medicine
Vellido Alcacena, Alfredo (Karger, 2019-02)
Article
Accés obertMedicine is becoming an increasingly data-centred discipline and, beyond classical statistical approaches, artificial intelligence (AI) and, in particular, machine learning (ML) are attracting much interest for the analysis ... -
Societal issues in machine learning: when learning from data is not enough
Bacciu, Davide; Biggio, Battista; Lisboa, Paulo J G; Martin Guerrero, Jose David; Oneto, Luca; Vellido Alcacena, Alfredo (European Symposium on Artificial Neural Networks (ESANN), 2019)
Comunicació de congrés
Accés obertIt has been argued that Artificial Intelligence (AI) is experiencing a fast process of commodification. Such characterization is on the interest of big IT companies, but it correctly reflects the current industrialization ... -
Studying embedded human EEG dynamics using generative topographic mapping
Vellido Alcacena, Alfredo; El-Deredy, W.; Lisboa, Paulo J G (2004-02)
Report de recerca
Accés obertA method has recently been proposed [1] to extract multiple signal source information from single-channel electroencephalogram (EEG) recordings. A dynamical systems approach is used to analyze the resulting EEG time series, ... -
SVM-based classification of class C GPCRs from alignment-free physicochemical transformations of their sequences
König, Caroline; Cruz Barbosa, Raúl; Alquézar Mancho, René; Vellido Alcacena, Alfredo (Springer Berlin Heidelberg, 2013)
Text en actes de congrés
Accés obertG protein-coupled receptors (GPCRs) have a key function in regulating the function of cells due to their ability to transmit extracelullar signals. Given that the 3D structure and the functionality of most GPCRs is unknown, ... -
Systematic analysis of primary sequence domain segments for the discrimination between class C GPCR subtypes
König, Caroline; Alquézar Mancho, René; Vellido Alcacena, Alfredo; Giraldo Arjonilla, Jesús (2018-03-01)
Article
Accés obertG-protein-coupled receptors (GPCRs) are a large and diverse super-family of eukaryotic cell membrane proteins that play an important physiological role as transmitters of extracellular signal. In this paper, we investigate ... -
The coming of age of interpretable and explainable machine learning models
Lisboa, Paulo; Saralajew, Sascha; Vellido Alcacena, Alfredo; Villmann, Thomas (I6doc.com, 2021)
Text en actes de congrés
Accés obertMachine learning-based systems are now part of a wide array of real-world applications seamlessly embedded in the social realm. In the wake of this realisation, strict legal regulations for these systems are currently being ... -
The effect of noise and sample size on an unsupervised feature selection method for manifold learning
Vellido Alcacena, Alfredo; Velazco, Jorge (IEEE, 2008)
Text en actes de congrés
Accés obertThe research on unsupervised feature selection is scarce in comparison to that for supervised models, despite the fact that this is an important issue for many clustering problems. An unsupervised feature selection method ... -
The extracellular N-terminal domain suffices to discriminate class C G Protein-Coupled Receptor subtypes from n-grams of their sequences
König, Caroline; Alquézar Mancho, René; Vellido Alcacena, Alfredo; Giraldo Arjonilla, Jesús (Institute of Electrical and Electronics Engineers (IEEE), 2015)
Text en actes de congrés
Accés obertThe investigation of protein functionality often relies on the knowledge of crystal 3-D structure. This structure is not always known or easily unravelled, which is the case of eukaryotic cell membrane proteins such as G ... -
The importance of interpretability and visualization in machine learning for applications in medicine and health care
Vellido Alcacena, Alfredo (2020)
Article
Accés obertIn a short period of time, many areas of science have made a sharp transition towards data-dependent methods. In some cases, this process has been enabled by simultaneous advances in data acquisition and the development ... -
The importance of interpretability and visualization in ML for medical applications
Vellido Alcacena, Alfredo (2021)
Comunicació de congrés
Accés obertMany areas of science have made a sharp transition towards data-dependent methods, enabled by simultaneous advances in data acquisition and the development of networked system technologies. This is particularly clear in ... -
The influence of alignment-free sequence representations on the semi-supervised classification of class C G protein-coupled receptors
Cruz Barbosa, Raúl; Vellido Alcacena, Alfredo; Giraldo Arjonilla, Jesús (2015-02-01)
Article
Accés obert -
Unfolding the Manifold in Generative Topographic Mapping
Cruz Barbosa, Raúl; Vellido Alcacena, Alfredo (2008-09)
Article
Accés restringit per política de l'editorialGenerative Topographic Mapping (GTM) is a probabilistic latent variable model for multivariate data clustering and visualization. It tries to capture the relevant data structure by defining a low-dimensional manifold ... -
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
Accés obertGlioblastoma 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 ... -
Using machine learning tools for protein database biocuration assistance
König, Caroline; Shaim, Ilmira; Vellido Alcacena, Alfredo; Romero Merino, Enrique; Alquézar Mancho, René; Giraldo Arjonilla, Jesús (Nature, 2018-07-05)
Article
Accés obertBiocuration in the omics sciences has become paramount, as research in these fields rapidly evolves towards increasingly data-dependent models. As a result, the management of web-accessible publicly-available databases ... -
Using random forests for assistance in the curation of G-protein coupled receptor databases
Shkurin, Aleksei; Vellido Alcacena, Alfredo (2017-08-18)
Article
Accés obertBackground: Biology is experiencing a gradual but fast transformation from a laboratory-centred science towards a data-centred one. As such, it requires robust data engineering and the use of quantitative data analysis ... -
Using single-voxel magnetic resonance spectroscopy data acquired at 1.5T to classify multivoxel data at 3T: a proof-of-concept study
Ungan, Gülnur; Pons Escoda, Albert; Ulinic, Daniel; Arus Caraltó, Carles; Vellido Alcacena, Alfredo; Julia Sape, Margarida (Multidisciplinary Digital Publishing Institute (MDPI), 2023-07-01)
Article
Accés obertIn vivo magnetic resonance spectroscopy (MRS) has two modalities, single-voxel (SV) and multivoxel (MV), in which one or more contiguous grids of SVs are acquired. Purpose: To test whether MV grids can be classified with ... -
Variational Bayesian generative topographic mapping
Olier Caparroso, Iván; Vellido Alcacena, Alfredo (2008-12)
Article
Accés restringit per política de l'editorialGeneral finite mixture models are powerful tools for the density-based grouping of multivariate i.i.d. data, but they lack data visualization capabilities, which reduces their practical applicability to real-world problems. ... -
Visual characterization of misclassified Class C GPCRs through Manifold-based machine learning methods
Cárdenas Domínguez, Martha Ivón; Vellido Alcacena, Alfredo; König, Caroline; Alquézar Mancho, René; Giraldo Arjonilla, Jesús (2015-09-18)
Article
Accés obertG-protein-coupled receptors are cell membrane proteins of great interest in biology and pharmacology. Previous analysis of Class C of these receptors has revealed the existence of an upper boundary on the accuracy that can ...