Exploració per autor "Vellido Alcacena, Alfredo"
Ara es mostren els items 92-111 de 129
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Network community cluster-based analysis for the identification of potential leukemia drug targets
(Springer, 2019)
Comunicació de congrés
Accés obertLeukemia is a hematologic cancer which develops in blood tissue and causes rapid generation of immature and abnormal-shaped white blood cells. It is one of the most prominent causes of death in both men and women for which ... -
NMF for quality control of multi-modal retinal images for diagnosis of diabetes mellitus and diabetic retinopathy
(Springer, 2022)
Text en actes de congrés
Accés obertIn current ophthalmology, images of the vascular system in the human retina are used as exploratory proxies for pathologies affecting different organs. In this brief paper, we use multi-modal retinal images for assisting ... -
On the benefits for model regularization of a variational formulation of GTM
(IEEE, 2008)
Text en actes de congrés
Accés obertGenerative Topographic Mapping (GTM) is a manifold learning model for the simultaneous visualization and clustering of multivariate data. It was originally formulated as a constrained mixture of distributions, for which ... -
On the computation of the geodesic distance with an application to dimensionality reduction in a neuro-oncology problem
(Springer, 2011)
Text en actes de congrés
Accés restringit per política de l'editorialManifold learning models attempt to parsimoniously describe multivariate data through a low-dimensional manifold embedded in data space. Similarities between points along this manifold are often expressed as Euclidean ... -
On the improvement of the mapping trustworthiness and continuity of a manifold learning model
(2008-11)
Article
Accés restringit per política de l'editorialManifold learningmethodsmodel high-dimensional data through low-dimensional manifolds embedded in the observed data space. This simplification implies that their are prone to trustworthiness and continuity errors. Generative ... -
On the use of graphical models to study ICU outcome prediction in septic patients treated with statins
(Springer, 2012)
Capítol de llibre
Accés restringit per política de l'editorial -
Physics and machine learning: Emerging paradigms
(I6doc.com, 2016)
Text en actes de congrés
Accés obertCurrent research in Machine Learning (ML) combines the study of variations on well-established methods with cutting-edge breakthroughs based on completely new approaches. Among the latter, emerging paradigms from Physics ... -
Predictive models in churn data mining: a review
(2007-01)
Report de recerca
Accés obertThe development of predictive models of customer abandonment plays a central role in any churn management strategy. These models can be developed using either qualitative approaches or can take a data-centred point of view. ... -
Preliminary theoretical results on a feature relevance determination method for Generative Topographic Mapping
(2005-04)
Report de recerca
Accés obertFeature selection (FS) has long been studied in classification and regression problems, following diverse approaches and resulting on a wide variety of methods, usually grouped as either /filters /or /wrappers/. In comparison, ... -
Preprocessing MRS information for classification of human brain tumours
(IGI Global, 2012-06)
Capítol de llibre
Accés restringit per política de l'editorial -
Probability ridges and distortion flows: Visualizing multivariate time series using a variational Bayesian manifold learning method
(Springer, 2014)
Text en actes de congrés
Accés obertTime-dependent natural phenomena and artificial processes can often be quantitatively expressed as multivariate time series (MTS). As in any other process of knowledge extraction from data, the analyst can benefit from the ... -
Radiomics-based assessment of optical coherence tomography angiography images for diabetic retinopathy diagnosis
(Elsevier, 2023-06)
Article
Accés obertPurpose: To evaluate the diagnostic accuracy of machine learning (ML) techniques applied to radiomic features extracted from OCT and OCT angiography (OCTA) images for diabetes mellitus (DM), diabetic retinopathy (DR), and ... -
Recognition of conformational states of a G protein coupled receptor from molecular dynamic simulations using sampling techniques
(Springer, 2023)
Text en actes de congrés
Accés restringit per política de l'editorialProtein structures are complex and dynamic entities relevant to many biological processes. G-protein-coupled receptors in particular are a functionally relevant family of cell membrane proteins of interest as targets in ... -
Reducing the n-gram feature space of class C GPCRs to subtype-discriminating patterns
(2014-10-23)
Article
Accés obertG protein-coupled receptors (GPCRs) are a large and heterogeneous superfamily of receptors that are key cell players for their role as extracellular signal transmitters. Class C GPCRs, in particular, are of great interest ... -
Robust cartogram visualization of outliers in manifold learning
(2013)
Text en actes de congrés
Accés obertMost real data sets contain atypical observations, often referred to as outliers. Their presence may have a negative impact in data modeling using machine learning. This is particularly the case in data density estimation ... -
Rule-based assistance to brain tumour diagnosis using LR-FIR
(2008-09)
Article
Accés restringit per política de l'editorialThis paper describes a process of rule-extraction from a multi-centre brain tumour database consisting of nuclear magnetic res- onance spectroscopic signals. The expert diagnosis of human brain tumours can benefit from ... -
Rule-based assistance to brain tumour diagnosis using LR-FIR
(Future Technology Press, 2009-01-31)
Capítol de llibre
Accés restringit per política de l'editorialThis paper describes a process of rule-extraction from a multi-centre brain tumour database consisting of nuclear magnetic res- onance spectroscopic signals. The expert diagnosis of human brain tumours can benefit from ... -
Seeing is believing: the importance of visualization in real-world machine learning applications
(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
(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
(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 ...
