Zobrazeno 1 - 10
of 250
pro vyhledávání: '"Mayo Íscar A"'
Real-world applications may be affected by outlying values. In the model-based clustering literature, several methodologies have been proposed to detect units that deviate from the majority of the data (rowwise outliers) and trim them from the parame
Externí odkaz:
http://arxiv.org/abs/2409.07881
Autor:
Luis Leal-Vega, M.ª Begoña Coco-Martín, Ainhoa Molina-Martín, Rubén Cuadrado-Asensio, Ana I. Vallelado-Álvarez, Hortensia Sánchez-Tocino, Agustín Mayo-Íscar, Carlos J. Hernández-Rodríguez, Juan F. Arenillas Lara, David P. Piñero
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract Immersive virtual reality (VR) is recently being explored as a therapeutic alternative for the treatment of amblyopia. This pilot study aimed to evaluate the preliminary efficacy, safety, usability and satisfaction obtained with the use of a
Externí odkaz:
https://doaj.org/article/fcb484b0dbaa41bb94cd7425e32c2655
Autor:
García-Escudero, Luis Angel, Hennig, Christian, Mayo-Iscar, Agustín, Morelli, Gianluca, Riani, Marco
So-called "classification trimmed likelihood curves" have been proposed as a useful heuristic tool to determine the number of clusters and trimming proportion in trimming-based robust clustering methods. However, these curves needs a careful visual i
Externí odkaz:
http://arxiv.org/abs/2309.08468
Autor:
Raúl López-Izquierdo, Carlos del Pozo Vegas, Ancor Sanz-García, Agustín Mayo Íscar, Miguel A. Castro Villamor, Eduardo Silva Alvarado, Santos Gracia Villar, Luis Alonso Dzul López, Silvia Aparicio Obregón, Rubén Calderon Iglesias, Joan B. Soriano, Francisco Martín-Rodríguez
Publikováno v:
npj Digital Medicine, Vol 7, Iss 1, Pp 1-8 (2024)
Abstract Emergency medical services (EMSs) face critical situations that require patient risk classification based on analytical and vital signs. We aimed to establish clustering-derived phenotypes based on prehospital analytical and vital signs that
Externí odkaz:
https://doaj.org/article/8a5c069b3a174edf884080c586a17a14
Akademický článek
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Autor:
del Barrio, Eustasio, Inouzhe, Hristo, Loubes, Jean-Michel, Matrán, Carlos, Mayo-Íscar, Agustín
Data obtained from Flow Cytometry present pronounced variability due to biological and technical reasons. Biological variability is a well-known phenomenon produced by measurements on different individuals, with different characteristics such as illn
Externí odkaz:
http://arxiv.org/abs/1907.08006
In this work a robust clustering algorithm for stationary time series is proposed. The algorithm is based on the use of estimated spectral densities, which are considered as functional data, as the basic characteristic of stationary time series for c
Externí odkaz:
http://arxiv.org/abs/1702.02165
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Akademický článek
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Many clustering algorithms when the data are curves or functions have been recently proposed. However, the presence of contamination in the sample of curves can influence the performance of most of them. In this work we propose a robust, model-based
Externí odkaz:
http://arxiv.org/abs/1701.03267