• Attraction-repulsion clustering: a way of promoting diversity linked to demographic parity in fair clustering 

  del Barrio, E.; Inouzhe, H.; Loubes, J.-M. (2022-10-20)

  We consider the problem of diversity enhancing clustering, i.e, developing clustering methods which produce clusters that favour diversity with respect to a set of protected attributes such as race, sex, age, etc. In the ...

• Automated location of orofacial landmarks to characterize airway morphology in anaesthesia via deep convolutional neural networks 

  García, F.; Lee, D.-J.; Mendoza-Garcés, F. J.; Irigoyen-Miró, S.; Legarreta-Olabarrieta, M. J.; García-Gutiérrez, S.; Arostegui, I. (2023-04)

  Background:A reliable anticipation of a difficult airway may notably enhance safety during anaesthesia. In current practice, clinicians use bedside screenings by manual measurements of patients’ morphology. Objective:To ...

• Extracting relevant predictive variables for COVID-19 severity prognosis: An exhaustive comparison of feature selection techniques 

  Hayet-Otero, M.; García, F.; Lee, D.-J.; Martínez-Minaya, J.; España Yandiola, P.P.; Urrutia Landa, I.; Nieves Ermecheo, M.; Quintana, J.M.; Menéndez, R.; Torres, A.; Zalacain Jorge, R.; Arostegui, I. (2023)

  With the COVID-19 pandemic having caused unprecedented numbers of infections and deaths, large research efforts have been undertaken to increase our understanding of the disease and the factors which determine diverse ...

• Variable selection in high-dimensional data: application in a SARS-CoV-2 pneumonia clinical data-set 

  Hayet-Otero, M. (2021-09-15)

  As a result of the COVID-19 pandemic that collapsed hospitals in some countries, numerous studies have been carried out to understand the development of the disease and how it affects patients with different characteristics, ...

• Development of machine learning system for airway prediction from facial image with mobile device 

  Mendoza Garcés, F.; García, F.; García, S.; García, B.; Vargas, J.; Lee, D.-J. (2022-06)

  Goals: A reliable prognostic tool for a difficult airway (DA) may enhance patients’ safety during orotracheal intubation by decreasing unanticipated DAs. We aim to examine the applicability of an Artificial Intelligence-Deep ...

• Desarrollo de sistema de Machine Learning para la prediccion de vía aérea a partir de imagen facial con dispositivo movil 

  Mendoza Garcés, F.; Irigoyen Miró, S.; García, F.; González, J.; García, S.; Telletxea, S. (2022-04)

  El manejo de una vía aérea difícil (VAD) representa aún una causa importante de lesiones relacionadas con la anestesia, cuyas complicaciones son potencialmente mortales. El notable interés en la predicción de VAD ha provocado ...

• Impacto cuantitativo de la contaminación en la probabilidad de muerte por neumonía por SARS-CoV-2 

  Bronte Moreno, O.; Urrutia Landa, I.; Martínez-Minaya, J.; García, F.; Lee, D.-J.; Jódar Samper, A.; García Hontoria, P.; Arostegui, I.; Artaraz Ereño, A.; Menéndez Villanueva, R.; Méndez Ocaña, R.; Torres Marti, A.; Cillóniz, C.; Zalacain Jorge, R.; Ruiz Iturriaga, L.A.; Serrano Fernández, L.; España Yandiola, P.P. (2021-11)

  Introducción La evidencia científica disponible señala que la contaminación del aire exterior podría agravar la severidad de la COVID-19 y por ende, incrementar las probabilidades de fallecimiento. Material y métodos Estudio ...

• Predicción de la gravedad de neumonías por SARS-CoV-2 a partir de información clínica y contaminación, mediante inteligencia artificial 

  Bronte Moreno, O.; Urrutia Landa, I.; García, F.; Martínez-Minaya, J.; Uranga Echeverria, A.; Lee, D.-J.; García Hontoria, P.; Jódar Samper, A.; Arostegui, I.; Menéndez Villanueva, R.; Méndez Ocaña, R.; Torres Marti, A.; Cillóniz, C.; Zalacain Jorge, R.; Ruiz Aldaiturriaga, L.A.; Serrano Fernández, L.; España Yandiola, P.P. (2021-11)

  Introducción La contaminación del aire exterior se ha relacionado con mayor gravedad de las infecciones respiratorias. Por tanto, su inclusión en algoritmos predictivos podrían añadir información para pronosticar la ...

• A two-stage approach for the spatio-temporal analysis of high-throughput phenotyping data 

  Pérez, D.M.; Rodríguez-Álvarez, M.X.; Boer, M.P; Kronenberg, L.; Hund, A.; Cabrera-Bosquet, L.; Millet, E.J.; van Eeuwijk, F.A. (2022-02-24)

  High throughput phenotyping (HTP) platforms and devices are increasingly used for the characterization of growth and developmental processes for large sets of plant genotypes. Such HTP data require challenging statistical ...

• Modeling latent spatio-temporal disease incidence using penalized composite link models 

  Lee, D.-J.; Durban, M.; Ayma, D.; Van de Kassteele, J. (2022-03-10)

  Epidemiological data are frequently recorded at coarse spatio-temporal resolutions to protect confidential information or to summarize it in a compact manner. However, the detailed patterns followed by the source data, ...

• Prediction of sports injuries in football: a recurrent time-to-event approach using regularized Cox models 

  Zumeta, L.; Weigert, M.; Larruskain, J.; Bikandi, E.; Setuain, I.; Lekue, J.; Küchenhoff, H.; Lee, D.-J. (2021-11-20)

  Data-based methods and statistical models are given special attention to the study of sports injuries to gain in-depth understanding of its risk factors and mechanisms. The objective of this work is to evaluate the use of ...

• A survey of bias in machine learning through the prism of statistical parity 

  Besse, P.; del Barrio, E.; Gordaliza, P.; Loubes, J.-M.; Risser, L. (2020)

  Applications based on machine learning models have now become an indispensable part of the everyday life and the professional world. As a consequence, a critical question has recently arose among the population: Do algorithmic ...

• Package wsbackfit for Smooth Backfitting Estimation of Generalized Structured Models 

  Roca-Pardinas, J.; Rodríguez-Álvarez, M.X.; Sperlich, S. (2021-01-01)

  A package is introduced that provides the weighted smooth backfitting estimator for a large family of popular semiparametric regression models. This family is known as generalized structured models, comprising, for example, ...

• ROCnReg: An R Package for Receiver Operating Characteristic Curve Inference With and Without Covariates 

  Rodríguez-Álvarez, M.X.; Vanda, I. (2021-01-01)

  This paper introduces the package ROCnReg that allows estimating the pooled ROC curve, the covariate-specific ROC curve, and the covariate-adjusted ROC curve by different methods, both from (semi) parametric and nonparametric ...

• Phenomics data processing: A plot-level model for repeated measurements to extract the timing of key stages and quantities at defined time points 

  Roth, L.; Van Eeuwijk, F.; Rodríguez-Álvarez, M.X.; Hans-Peter, P.; Hund, A. (2021)

  Decision-making in breeding increasingly depends on the ability to capture and predict crop responses to changing environmental factors. Advances in crop modeling as well as high-throughput eld phenotyping (HTFP) hold ...

• Simulation approach for assessing the performance of the γEWMA control chart 

  Patino-Rodriguez, C.; Pérez, D. M.; Usuga Manco, O. (2021-02-22)

  i) Purpose: The purpose of this paper is to evaluate the performance of a modified EWMA control chart ($\gamma$EWMA control chart), which considers data distribution and incorporate its correlation structure, simulating ...

• Altered effective connectivity in sensorimotor cortices: a novel signature of severity and clinical course in depression 

  Ray, D.; Bezmaternykh, D.; Mel'nikov, M.; Friston, K.J.; Das, M. (2021)

  Functional neuroimaging research on depression has traditionally targeted neural networks associated with the psychological aspects of depression. In this study, instead, we focus on alterations of sensorimotor function ...

• From habitat to management: a simulation framework for improving statistical methods in fisheries science 

  Citores Martínez, L. (2021-07-07)

  Monte Carlo simulation consists of computer experiments that involve creating data by pseudo-random sampling and has shown to be a powerful tool for studying the performance of statistical methods. In this thesis Monte ...

• Optimal experimental design for cytogenetic dose-response calibration curves 

  Higueras, M.; Howes, A.; López, J. (2019)

  Purpose: To introduce optimal experimental design techniques in the cytogenetic biological dosimetry practice. This includes the development of a new optimality criterion for the calibration of radiation doses. Materials ...

• Spatial Bayesian Modeling Applied to the Surveys of Xylella fastidiosa in Alicante (Spain) and Apulia (Italy) 

  Cendoya, M.; Martínez-Minaya, J.; Dalmau, V.; Ferrer, A.; Saponari, M.; Conesa, D.; López-Quílez, A.; Vicent, A. (2020)

  The plant-pathogenic bacterium Xylella fastidiosa was first reported in Europe in 2013, in the province of Lecce, Italy, where extensive areas were affected by the olive quick decline syndrome, caused by the subsp. pauca. ...

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