Examinando por Autor "Rojo-Álvarez, José Luis"

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A Big Data Approach to Customer Relationship Management Strategy in Hospitality Using Multiple Correspondence Domain Description
(MDPI, 2020-12-29) González-Serrano, Lydia; Talón-Ballestero, Pilar; Muñoz-Romero, Sergio; Soguero-Ruiz, Cristina; Rojo-Álvarez, José Luis
COVID-19 has hit the hotel sector in a hitherto unknown way. This situation is producing a fundamental change in client behavior that makes crucial an adequate knowledge of their profile to overcome an uncertain environment. Customer Relationship Management (CRM) can provide key strategies in hospitality industry by generating a great amount of valuable information about clients, whereas Big Data tools are providing with unprecedented facilities to conduct massive analysis and to focus the client-to-business relationship. However, few instruments have been proposed to handle categorical features, which are the most usual in CRMs, aiming to adapt the statistical robustness with the best interpretability for the managers. Therefore, our aim was to identify the profiles of clients from an international hotel chain using the overall data in its CRM system. An analysis method was created involving three elements: First, Multiple Correspondence Analysis provides us with a statistical description of the interactions among categories and features. Second, bootstrap resampling techniques give us information about the statistical variability of the feature maps. Third, kernel methods provide easy-to-visualize domain descriptions based on confidence areas in the maps. The proposed methodology can provide an operative and statistically principled way to scrutinize the CRM profiles in hospitality.
A New Algorithm for Rhythm Discrimination in Cardioverter Defibrillators Based on the Initial Voltage Changes of the Ventricular Electrogram
(2009-07-23T08:37:22Z) Rojo-Álvarez, José Luis; Arenal Maíz, Ángel; García Alberola, A; Ortiz, M; Valdés, M; Artés Rodríguez, A
A New Method for Single-Step Robust Post-Processing of Flow Color Doppler M-Mode Images Using Support Vector Machines
(2009-06-15T10:08:10Z) Conde Pardo, P; Guerrero Curieses, A; Rojo-Álvarez, José Luis; Yotti, R; Requena Carrión, J; Antoranz, José Carlos; Bermejo, Javier
Intra-cardiac pressure gradients (ICPG) are usually es timated by post-processing of flow Color Doppler M-mode images (CDMMI) by using a sequence of processing steps. We propose a novel image processing method which gives a single-step approximation of the ICPG image, based on a simple, yet specifically developed, Support Vector Machine (SVM) algorithm. Our method only requires the SVM estimation of the blood velocity from the CDMMI. Given that ICPG images are obtained by deterministic operators (Euler's momentum equation) on the blood velocity, the ICPG estimation is a simple model that consists of the same coefficients and the operator applied to the Mercer's kernel. A diverse-width Mercer's kernel is proposed, as an alternative to conventional Radial Basis Function kernel. Simulations on a synthetic model and approximations of a real example image, trained with up to 10% of the pixels, show the possibilities of this new single-step postprocessing method.
A Noninvasive Method for Assessing Impaired Diastolic Suction in Patients With Dilated Cardiomyopathy
(2009-07-14T11:31:16Z) Yotti, R; Bermejo, Javier; Antoranz, José Carlos; Desco, Mar; Cortina, Cristina; Rojo-Álvarez, José Luis; Allué, Carmen; Martín, Laura; Moreno, Mar; Serrano, JA; Muñoz, Roberto; García Fernández, MA
A Resampling Univariate Analysis Approach to Ovarian Cancer from Clinical and Genetic Data
(IEEE, 2021-02-08) Bote-Curiel, Luis; Ruiz-Llorente, Sergio; Muñoz-Romero, Sergio; Yagüe-Fernández, Mónica; Barquín, Arantzazu; García-Donas, Jesús; Rojo-Álvarez, José Luis
Ovarian cancer (OC) is the second most common gynecological malignancy and the gynecological tumor with the worst prognosis. To try to improve this situation, Data Science technologies could be a useful tool to help clinicians to know more about the disease. In our case, we are interested in exploring OC data to discover relationships between clinical and genetic factors and the disease progression. For it, we propose an analysis framework for simple and univariate statistical descriptions of features of different types, based on bootstrap resampling. Foremost, we define the framework for metric, categorical, and dates variables and determine what are the advantages and disadvantages of using different bootstrap resampling strategies, based on their statistical basis. Then, we use it to perform a univariate analysis over an OC dataset that allows to explore how is the disease progression, having platinum-free interval as indicator, in relation to clinical and genetic features of different types. Also, it provides a first set of variables possibly relevant for survival prediction. Results obtained show that some features have led to individual differences between both platinum resistant (<; 6 months) and platinum sensitive(>6 months) groups. It can be concluded that this could be an indicator that the database could be discriminatory for the hypotheses studied, though it is convenient to make multivariate analyses to check how relationships among features are influenced.
A Review on Recent Patents in Digital Processing for Cardiac Electric Signals (I): From Basic Systems to Arrhythmia Analysis
(2009-07-14T11:06:21Z) Goya Esteban, R; Barquero Pérez, Óscar; Alonso Atienza, Felipe; Everss, E; Requena Carrión, Jesús; García Alberola, Arcadi; Rojo-Álvarez, José Luis
Cardiac electric signals are currently the most informative source about the heart rhythm and its disorders, and hence, the use of adequate digital signal processing techniques is necessary to yield reliable diagnostic parameters, either to the clinician or to automatic monitoring systems. A number of systems have been patented during the last years, which are grouped in this review according to their application scope. In this first part, techniques for electrocardiogram and intracardiac electrogram filtering, and for feature extraction, are first examined, then patents on arrhythmia analysis are then summarized. The wide number of basic systems for cardiac signal processing analysis that have been disclosed indicates that this field represents a main scenario in the near and middle future of cardiac health.
A Review on Recent Patents in Digital Processing for Cardiac Electric Signals (II): Advanced Systems and Applications
(2009-07-14T11:13:08Z) Barquero Pérez, Óscar; Goya Esteban, R; Alonso Atienza, Felipe; Requena Carrión, Jesús; Everss, E; García Alberola, Arcadi; Rojo-Álvarez, José Luis
Digital signal processing algorithms for cardiac recordings have been paid much attention in recently disclosed patents. In this second part of our review of the state-of-art patents, systems for sudden cardiac death prediction, as well as for apnea analysis, are summarized. Advanced digital signal processing algorithms for cardiac electric signals are specifically reviewed, including independent component decompositions, and nonlinear methods (chaos, fractals, and entropies). Finally, systems aiming to solve the inverse problem in electrocardiography are presented. Concluding remarks on these systems and on the whole review are discussed.
A Robust Support Vector Algorithm for Nonparametric Spectral Analysis
(2009-02-04T19:11:51Z) Rojo-Álvarez, José Luis; Martínez Ramón, Manel; Figueiras Vidal, Aníbal R; García Armada, Ana; Artés Rodríguez, Antonio
A new approach to the nonparametric spectral estimation on the basis of the support vector method (SVM) framework is presented. A reweighted least squared error formulation avoids the computational limitations of quadratic programming. The application to a synthetic example and to a digital communication problem shows the robustness of the SVM spectral analysis algorithm.
A systematic Review of the Literature on Home Monitoring for Patients with Heart Failure
(2009-07-02T11:09:54Z) Martínez Fernández, A; Everss, E; Rojo-Álvarez, José Luis; Pascual Figal, Domingo; García Alberola, A
Action Potential Alternans in LQT3 Syndrome: A Simulation Study
(2009-06-15T09:26:47Z) Alonso Atienza, Felipe; Requena Carrión, J; Rojo-Álvarez, José Luis; Berenfeld, O; Jalife, J
The long QT syndrome type-3 (LQT3) is an inherited cardiac disorder caused by mutations in the sodium channel gene SCN5A. LQT3 has been associated with ventricular arrhythmias and sudden cardiac death, specially at low heart rates. Based on computer simulations and experimental investigations, analysis of the morphology of the Action Potential (AP) has shown that it undergoes early afterdepolarizations (EADs) and spontaneous discharges, which are thought to be the trigger for reentry like-activity. However, dynamic characteristics of cardiac tissue are also important factors of arrhythmia mechanisms. In this work, we propose a dynamical analysis of the LQT3 at cellular level. We use a detailed Markovian model of the DKPQ mutation, which is associated with LQT3, and we study beat-to-beat AP Duration (APD) variations by using a long-term stimulation protocol. Compared to wild-type (WT) cells, DKPQ mutant cells are found to develop APD alternans over a narrow range of stimulation frequencies. Moreover, the interval of frequency dependence of APD alternans is related to the degree of severity of the EADs present in the AP. In conclusion, dynamical analysis of paced cells is a useful approach to understand the mechanisms of rate dependent arrhythmias.
AKPQ mutation in LQT3 results in increased frequency and stability of reentry
(2009-07-28T10:25:27Z) Alonso Atienza, Felipe; Requena Carrión, Jesús; Rojo-Álvarez, José Luis; Berenfeld, O; Jalife, J
Analysing Effects of Implant Dimensions on Electrocardiograph: A Modeling Approach
(2009-06-15T09:22:13Z) Väisänen, J; Requena Carrión, J; Alonso Atienza, Felipe; Rojo-Álvarez, José Luis; Hyttinen, J
Modeling offers effective means of studying the effects of implant dimensions on the measured electrocardiograph (ECG) prior to any in vivo tests, and thus provides the designer with valuable information. Finite difference (FDM) and lead field approaches combined with cardiac activation models offer straightforward and effective methods for analyzing different ECG measurement configurations. In the present study such methods are applied in studying the effects of implant dimensions on the simulated ECG which describes an ectopic beat originating from the apex. The results indicated that the change in interelectrode distance has the largest effects on the ECG. Other parameters related implant dimensions have minor effect on the ECG.
Analysis of Physiological Meaning of Detrended Fluctuation Analysis in Heart Rate Variability Using a Lumped Parameter Model
(2009-06-15T10:04:05Z) Rojo-Álvarez, José Luis; Sánchez Sánchez, A; Barquero Pérez, Óscar; Goya Esteban, R; Everss, E; Mora Jimenez, I; García Alberola, A
Chaos and fractal based measurements, such as Detrended Fluctuation Analysis (DFA), have been widely used for quantifying the Heart Rate Variability (HRV) for cardiac risk stratification purposes. However, the physiological meaning of these measurements is not clear. Given that existing lumped parameter models contain a detailed physiological description of several of the circulatory system regulation processes, we hypothesize that controlled changes in these processes will highlight the physiological basis in DFA indices. We used a detailed lumped parameter model of HRV, introduced earlier [6]. Ten signals were generated in different physiological conditions. DFA coefficients 1, 2, and the Hurst exponent, were calculated. A clear disruption point was always observed. Modifications in sympatho-vagal activity yielded significant changes in 1 when compared to basal, but not in 2 or Hurst exponent. Modifications in non-nervous system mediated changes yielded significant differences only for peripheral resistance and heart period, only in 1. In conclusion, the analysis of the effect of changes in the regulatory system on the HRV chaotic/fractal indices can be analyzed using detailed lumped parameter models
Analysis of the Scope of Unipolar and Bipolar Electrograms in Implantable Cardioverter Defibrillators
(2009-07-23T10:51:41Z) Requena Carrión, Jesús; Väisänen, J; Hyttinen, J; Rojo-Álvarez, José Luis; Alonso Atienza, Felipe; Malmivuo, J
Assessing the Impact of Temporary Retail Price Discounts Intervals Using SVM Semiparametric Regression
(2009-07-14T10:46:24Z) Martínez Ruiz, María Pilar; Mollá Descals, Alejandro; Gómez Borja, M.A; Rojo-Álvarez, José Luis
Although the marketing literature has found that temporary retail price discounts cause a significant sales increase, little is known about the specific characteristics of deals that influence the magnitude of the sales spike. In this paper, we analyse the impact of the length of temporary retail price discounts periods on the sales increase using scanner-store daily-sales data for two frequently purchased product categories: ground coffee (a storable category) and yogurt (a perishable category).Wedevelop a robust semiparametric regression model based on support vector statistical theory with several previously proposed predictors along with a daily time description. This model also makes it possible to investigate the impact of temporary retail price reductions on own-andcompeting brand sales, observing brand substitution patterns. The results evidence: (1) which days of the promotional period present a higher contribution to the sales spike; (2) the existence of threshold and saturation effects; and (3) that asymmetric cross price effects apply in both categories.
Avoiding food waste from restaurant tickets: a big data management tool
(Emerald Publishing Limited, 2024-03-05) Gómez-Talal, Ismael; González-Serrano, Lydia; Rojo-Álvarez, José Luis; Talón-Ballestero, Pilar
Purpose This study aims to address the global food waste problem in restaurants by analyzing customer sales information provided by restaurant tickets to gain valuable insights into directing sales of perishable products and optimizing product purchases according to customer demand. Design/methodology/approach A system based on unsupervised machine learning (ML) data models was created to provide a simple and interpretable management tool. This system performs analysis based on two elements: first, it consolidates and visualizes mutual and nontrivial relationships between information features extracted from tickets using multicomponent analysis, bootstrap resampling and ML domain description. Second, it presents statistically relevant relationships in color-coded tables that provide food waste-related recommendations to restaurant managers. Findings The study identified relationships between products and customer sales in specific months. Other ticket elements have been related, such as products with days, hours or functional areas and products with products (cross-selling). Big data (BD) technology helped analyze restaurant tickets and obtain information on product sales behavior. Research limitations/implications This study addresses food waste in restaurants using BD and unsupervised ML models. Despite limitations in ticket information and lack of product detail, it opens up research opportunities in relationship analysis, cross-selling, productivity and deep learning applications. Originality/value The value and originality of this work lie in the application of BD and unsupervised ML technologies to analyze restaurant tickets and obtain information on product sales behavior. Better sales projection can adjust product purchases to customer demand, reducing food waste and optimizing profits.
Bootstrap Feature Selection in Support Vector Machines for Ventricular Fibrillation Detection
(2009-07-23T11:01:23Z) Alonso Atienza, Felipe; Rojo-Álvarez, José Luis; Camps Valls, Gustavo; Rosado Muñoz, A; García Alberola, A
Support Vector Machines (SVM) for classification are being paid special attention in a number of practical applications. When using nonlinear Mercer kernels, the mapping of the input space to a highdimensional feature space makes the input feature selection a difficult task to be addressed. In this paper, we propose the use of nonparametric bootstrap resampling technique to provide with a statistical, distribution independent, criterion for input space feature selection. The confidence interval of the difference of error probability between the complete input space and a reduced-in-one-variable input space, is estimated via bootstrap resampling. Hence, a backward variable elimination procedure can be stated, by removing one variable at each step according to its associated confidence interval. A practical example application to early stage detection of cardiac Ventricular Fibrillation (VF) is presented. Basing on a previous nonlinear analysis based on temporal and spectral VF parameters, we use the SVM with Gaussian kernel and bootstrap resampling to provide with the minimum input space feature set that still holds the classification performance of the complete data. The use of bootstrap resampling is a powerful input feature selection procedure for SVM classifiers.
Caracterización no invasiva de la contractilidad miocárdica mediante el análisis de los gradientes de presión intraventricular derivados de imágenes de Doppler-color
(2009-07-28T10:11:23Z) Yotti, R; Bermejo, Javier; Desco, Mar; Cortina, Cristina; Antoranz, José Carlos; Rojo-Álvarez, José Luis; Moreno, Mar; García Fernández, MA
Changes in Cardiac Indices from Implanted Defibrillator-Stored Electrograms Due to Acquisition and Preprocessing Conditions
(2009-06-15T09:41:57Z) Requena Carrión, J; Rojo-Álvarez, José Luis; Everss, E; Alonso Atienza, Felipe; Sánchez Muñoz, JJ; Ortiz, M; García Alberola, A
A wide number of cardiac indices have been proposed to describe electrocardiograms (ECG) during ventricular Fibrillation (VF), and they can be useful when analyzing electrograms (EGM) stored in Implantable Cardioverter Defibrillator (ICD) during spontaneous VF. However, the dependence of their measurement on acquisition and preprocessing conditions has not been so far statistically quantified. We propose a systematic procedure based on nonparametric bootstrap resampling methods to obtain standard errors and confidence intervals for a test. This test detects changes in the statistical distribution of cardiac indices from ICD-stored EGM during VF, due to discrepancies in acquisition and preprocessing conditions. As an application example, significant changes in the distributions of selected spectral indices due to lead configuration were found by comparing measurements obtained from simultaneo usly recorded unipolar and bipolar EGM during VF. Our nonparametric bootstrap approach can be readily applied to the measurement of cardiac indices, allowing us to study their changes under a diversity of conditions in a systematic way.
Changes in Detrended Fluctuation Indices with Aging in Healthy and Congestive Heart Failure Subjects
(2009-06-15T09:01:00Z) Barquero Pérez, Óscar; Marqués de Sa, J; Rojo-Álvarez, José Luis; Goya Esteban, R
Detrended Fluctuation Analysis (DFA) aims to quantify the fractal correlation properties in nonstationary time series, and it has successfully been applied in the assessment of the Heart Rate Variability (HRV) for cardiac risk stratification purposes. However the physiological meaning of DFA indices and its relation with aging have not yet been completely established. Given that a loss of complexity in the physiological regulation of elderly subjects has been reported in the literature, we hypothesized that DFA indices could be modified by aging. In this work we computed the Hurst exponent (estimated using DFA method) and DFA indices alfa1 and alfa2 to assess the HRV in healthy and Congestive Heart Failure (CHF) subjects, and we studied the dependence of these indices on aging for both healthy and CHF subjects. We found that only alfa2 and Hurst exponent, and only in the case of healthy subjects, have significant discrimination capability to distinguish between young and elderly groups, and also that these indices have a steady increase with aging. Therefore, we can conclude that the loss of complexity due to aging can be quantified by changes in the values of alfa2 and Hurst exponent.