Zobrazeno 1 - 10
of 88
pro vyhledávání: '"Gerardo Sanz"'
Autor:
Ángel Borque-Fernando, Fernando Estrada-Domínguez, Luis Mariano Esteban, María Jesús Gil-Sanz, Gerardo Sanz
Publikováno v:
The World Journal of Men's Health, Vol 41, Iss 1, Pp 129-141 (2023)
Purpose: To analyze the variability, associated actors, and the design of nomograms for individualized testosterone recovery after cessation of androgen deprivation therapy (ADT). Materials and Methods: A longitudinal study was carried out with 208
Externí odkaz:
https://doaj.org/article/e4eb7fd5764045d6bb08e5f3ccf69434
Autor:
Miguel Lafuente, Francisco Javier López, Pedro Mariano Mateo, Ana Carmen Cebrián, Jesús Asín, José Antonio Moler, Ángel Borque-Fernando, Luis Mariano Esteban, Ana Pérez-Palomares, Gerardo Sanz
Publikováno v:
Heliyon, Vol 9, Iss 2, Pp e13545- (2023)
Objective: This study aims to build a multistate model and describe a predictive tool for estimating the daily number of intensive care unit (ICU) and hospital beds occupied by patients with coronavirus 2019 disease (COVID-19). Material and methods:
Externí odkaz:
https://doaj.org/article/c8520ec57ba04a0c81f0faa80eba7055
Autor:
Luis Mariano Esteban, Berta Castán, Javier Esteban-Escaño, Gerardo Sanz-Enguita, Antonio R. Laliena, Ana Cristina Lou-Mercadé, Marta Chóliz-Ezquerro, Sergio Castán, Ricardo Savirón-Cornudella
Publikováno v:
Applied Sciences, Vol 13, Iss 13, p 7478 (2023)
Electronic fetal monitoring (EFM) is widely used in intrapartum care as the standard method for monitoring fetal well-being. Our objective was to employ machine learning algorithms to predict acidemia by analyzing specific features extracted from the
Externí odkaz:
https://doaj.org/article/80ba1927727a4b5794c8a092b0285334
Publikováno v:
Symmetry, Vol 15, Iss 3, p 756 (2023)
Although linearly combining multiple variables can provide adequate diagnostic performance, certain algorithms have the limitation of being computationally demanding when the number of variables is sufficiently high. Liu et al. proposed the min–max
Externí odkaz:
https://doaj.org/article/bb8d30e0be274d98a8e4abcdebdfdb5b
Publikováno v:
Mathematics, Vol 10, Iss 14, p 2442 (2022)
Given a sequence (Xn) of random variables, Xn is said to be a near-record if Xn∈(Mn−1−a,Mn−1], where Mn=max{X1,…,Xn} and a>0 is a parameter. We investigate the point process η on [0,∞) of near-record values from an integer-valued, indepe
Externí odkaz:
https://doaj.org/article/5d107c053ea54865898003a25d029cd7
Autor:
Javier Esteban-Escaño, Berta Castán, Sergio Castán, Marta Chóliz-Ezquerro, César Asensio, Antonio R. Laliena, Gerardo Sanz-Enguita, Gerardo Sanz, Luis Mariano Esteban, Ricardo Savirón
Publikováno v:
Entropy, Vol 24, Iss 1, p 68 (2021)
Background: Electronic fetal monitoring (EFM) is the universal method for the surveillance of fetal well-being in intrapartum. Our objective was to predict acidemia from fetal heart signal features using machine learning algorithms. Methods: A case
Externí odkaz:
https://doaj.org/article/00bd7923531141429a1e526ae56d0185
Autor:
Rocío Aznar-Gimeno, Luis M. Esteban, Rafael del-Hoyo-Alonso, Ángel Borque-Fernando, Gerardo Sanz
Publikováno v:
Mathematics, Vol 10, Iss 8, p 1221 (2022)
Combining multiple biomarkers to provide predictive models with a greater discriminatory ability is a discipline that has received attention in recent years. Choosing the probability threshold that corresponds to the highest combined marker accuracy
Externí odkaz:
https://doaj.org/article/8da2e02c35204236bf51c4e8b9d32a4a
Autor:
Rocío Aznar-Gimeno, Luis M. Esteban, Gerardo Sanz, Rafael del-Hoyo-Alonso, Ricardo Savirón-Cornudella
Publikováno v:
Mathematics, Vol 9, Iss 19, p 2497 (2021)
Linearly combining multiple biomarkers is a common practice that can provide a better diagnostic performance. When the number of biomarkers is sufficiently high, a computational burden problem arises. Liu et al. proposed a distribution-free approach
Externí odkaz:
https://doaj.org/article/91881105733a4bc4a2649c1d661dc71d
Autor:
Savirón-Cornudella, Luis Mariano Esteban, Berta Castán, Javier Esteban-Escaño, Gerardo Sanz-Enguita, Antonio R. Laliena, Ana Cristina Lou-Mercadé, Marta Chóliz-Ezquerro, Sergio Castán, Ricardo
Publikováno v:
Applied Sciences; Volume 13; Issue 13; Pages: 7478
Electronic fetal monitoring (EFM) is widely used in intrapartum care as the standard method for monitoring fetal well-being. Our objective was to employ machine learning algorithms to predict acidemia by analyzing specific features extracted from the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::45474a3e72f49378773990ef8b28bc16
Publikováno v:
Trends in Mathematical, Information and Data Sciences ISBN: 9783031041365
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6cb1e7ccbce3394a5ccc02f01b55f9c9
https://doi.org/10.1007/978-3-031-04137-2_8
https://doi.org/10.1007/978-3-031-04137-2_8
