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8,561 results on '"Alonso María"'

1. On Fidel Vakarelov construction for Monadic Godel algebras

Author

Alonso, Maria Valentina and Pelaitay, Gustavo

Subjects
Mathematics - Logic
Abstract

A significant correlation between Nelson algebras and Heyting algebras has been explored by several scholars, including Cignoli, Fidel, Vakarelov, and Sendlewski. This connection is integral to the concept of twist structures, whose origins can be traced back to the work of Kalman. In this paper, we obtain an expansion of the Fidel-Vakarelov construction, applying it to monadic Godel algebras (or monadic prelinear Heyting algebras). This extension leads to the emergence of a new variety, which we aptly term monadic prelinear Nelson algebras., Comment: arXiv admin note: text overlap with arXiv:1708.09490 by other authors

Published
2024

3. A translational framework to DELIVER nanomedicines to the clinic

Author

Joyce, Paul, Allen, Christine J., Alonso, María José, Ashford, Marianne, Bradbury, Michelle S., Germain, Matthieu, Kavallaris, Maria, Langer, Robert, Lammers, Twan, Peracchia, Maria Teresa, Popat, Amirali, Prestidge, Clive A., Rijcken, Cristianne J. F., Sarmento, Bruno, Schmid, Ruth B., Schroeder, Avi, Subramaniam, Santhni, Thorn, Chelsea R., Whitehead, Kathryn A., Zhao, Chun-Xia, and Santos, Hélder A.

Published
2024
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5. Application of Machine Learning Algorithms in Classifying Postoperative Success in Metabolic Bariatric Surgery: A Comprehensive Study

Author

Benítez-Andrades, José Alberto, Prada-García, Camino, García-Fernández, Rubén, Ballesteros-Pomar, María D., González-Alonso, María-Inmaculada, and Serrano-García, Antonio

Subjects
Computer Science - Machine Learning, Quantitative Biology - Quantitative Methods
Abstract

Objectives: Metabolic Bariatric Surgery (MBS) is a critical intervention for patients living with obesity and related health issues. Accurate classification and prediction of patient outcomes are vital for optimizing treatment strategies. This study presents a novel machine learning approach to classify patients in the context of metabolic bariatric surgery, providing insights into the efficacy of different models and variable types. Methods: Various machine learning models, including GaussianNB, ComplementNB, KNN, Decision Tree, KNN with RandomOverSampler, and KNN with SMOTE, were applied to a dataset of 73 patients. The dataset, comprising psychometric, socioeconomic, and analytical variables, was analyzed to determine the most efficient predictive model. The study also explored the impact of different variable groupings and oversampling techniques. Results: Experimental results indicate average accuracy values as high as 66.7% for the best model. Enhanced versions of KNN and Decision Tree, along with variations of KNN such as RandomOverSampler and SMOTE, yielded the best results. Conclusions: The study unveils a promising avenue for classifying patients in the realm of metabolic bariatric surgery. The results underscore the importance of selecting appropriate variables and employing diverse approaches to achieve optimal performance. The developed system holds potential as a tool to assist healthcare professionals in decision-making, thereby enhancing metabolic bariatric surgery outcomes. These findings lay the groundwork for future collaboration between hospitals and healthcare entities to improve patient care through the utilization of machine learning algorithms. Moreover, the findings suggest room for improvement, potentially achievable with a larger dataset and careful parameter tuning.

Published
2024
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6. Survival and grade of the glioma prediction using transfer learning

Author

Rubio, Santiago Valbuena, García-Ordás, María Teresa, Olivera, Oscar García-Olalla, Alaiz-Moretón, Héctor, González-Alonso, Maria-Inmaculada, and Benítez-Andrades, José Alberto

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

Glioblastoma is a highly malignant brain tumor with a life expectancy of only 3 to 6 months without treatment. Detecting and predicting its survival and grade accurately are crucial. This study introduces a novel approach using transfer learning techniques. Various pre-trained networks, including EfficientNet, ResNet, VGG16, and Inception, were tested through exhaustive optimization to identify the most suitable architecture. Transfer learning was applied to fine-tune these models on a glioblastoma image dataset, aiming to achieve two objectives: survival and tumor grade prediction.The experimental results show 65% accuracy in survival prediction, classifying patients into short, medium, or long survival categories. Additionally, the prediction of tumor grade achieved an accuracy of 97%, accurately differentiating low-grade gliomas (LGG) and high-grade gliomas (HGG). The success of the approach is attributed to the effectiveness of transfer learning, surpassing the current state-of-the-art methods. In conclusion, this study presents a promising method for predicting the survival and grade of glioblastoma. Transfer learning demonstrates its potential in enhancing prediction models, particularly in scenarios with limited large datasets. These findings hold promise for improving diagnostic and treatment approaches for glioblastoma patients.

Published
2024
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10. Antimicrobial resistance in food-associated Escherichia coli in Mexico and Latin America.

Author

Babines-Orozco, Lorena, Balbuena-Alonso, María, Barrios-Villa, Edwin, Lozano-Zarain, Patricia, Martínez-Laguna, Ygnacio, Del Carmen Rocha-Gracia, Rosa, and Cortés-Cortés, Gerardo

Subjects
Escherichia coli, Latin America, Mexico, antimicrobial resistance, food
Abstract

The World Health Organization (WHO) considers antimicrobial resistance to be one of the critical global public health priorities to address. Escherichia coli is a commensal bacterium of the gut microbiota in humans and animals; however, some strains cause infections and are resistant to antibiotics. One of the most common ways of acquiring pathogenic E. coli strains is through food. This review analyzes multidrug-resistant E. coli isolated from food, emphasizing Latin America and Mexico, and the mobile genetic elements (MGEs) responsible for spreading antibiotic resistance determinants among bacteria in different environments and hosts. We conducted a systematic search of the literature published from 2015 to 2022 in open access databases and electronic repositories. The prevalence of 11 E. coli pathotypes was described, with diarrheagenic E. coli pathotypes being the most frequently associated with foodborne illness in different Latin American countries, highlighting the presence of different antibiotic resistance genes mostly carried by IncF-type plasmids or class 1 integrons. Although the global incidence of foodborne illness is high, there have been few studies in Mexico and Latin America, which highlights the need to generate updated epidemiological data from the One Health approach, which allows monitoring of the multidrug-resistance phenomenon in E. coli from a common perspective in the interaction of human, veterinary, and environmental health.

Published
2024

13. Author Correction: Modulating the immune response to SARS-CoV-2 by different nanocarriers delivering an mRNA expressing trimeric RBD of the spike protein: COVARNA Consortium

Author

Marcos-Villar, Laura, Perdiguero, Beatriz, Anthiya, Shubaash, Borrajo, Mireya L., Lou, Gustavo, Franceschini, Lorenzo, Esteban, Ignasi, Sánchez-Cordón, Pedro J., Zamora, Carmen, Sorzano, Carlos Óscar S., Jordá, Luis, Codó, Laia, Gelpí, Josep L., Sisteré-Oró, Marta, Meyerhans, Andreas, Thielemans, Kris, Martínez-Jiménez, Francisco, López-Bigas, Núria, García, Felipe, Alonso, María J., Plana, Montserrat, Esteban, Mariano, and Gómez, Carmen Elena

Published
2024
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14. Perception of pregnant individuals, health providers and decision makers on interventions to cease substance consumption during pregnancy: a qualitative study

Author

Vila-Farinas, Andrea, Pérez-Ríos, Mónica, Montes-Martínez, Agustín, Ahluwalia, Jasjit S-, Mourino, Nerea, Rey-Brandariz, Julia, Triñanes-Pego, Yolanda, Candal-Pedreira, Cristina, Ruano-Ravina, Alberto, Gómez-Salgado, Patricia, Miguez-Varela, Carmen, Tajes-Alonso, María, Loureiro-Fuentes, Isabel, Riesgo-Martín, Juan, Valverde-Trillo, Araceli, Fernández-Lema, Isabel, Rey-Arijón, Mercedes, Freiría-Somoza, Isabel, Rodríguez-Pampín, María, and Varela-Lema, Leonor

Published
2024
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16. Modulating the immune response to SARS-CoV-2 by different nanocarriers delivering an mRNA expressing trimeric RBD of the spike protein: COVARNA Consortium

Author

Marcos-Villar, Laura, Perdiguero, Beatriz, Anthiya, Shubaash, Borrajo, Mireya L., Lou, Gustavo, Franceschini, Lorenzo, Esteban, Ignasi, Sánchez-Cordón, Pedro J., Zamora, Carmen, Sorzano, Carlos Óscar S., Jordá, Luis, Codó, Laia, Gelpí, Josep L., Sisteré-Oró, Marta, Meyerhans, Andreas, Thielemans, Kris, Martínez-Jiménez, Francisco, López-Bigas, Núria, García, Felipe, Alonso, María J., Plana, Montserrat, Esteban, Mariano, and Gómez, Carmen Elena

Published
2024
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17. The effect of a cognitive training therapy based on stimulation of brain oscillations in patients with mild cognitive impairment in a Chilean sample: study protocol for a phase IIb, 2 × 3 mixed factorial, double-blind randomised controlled trial

Author

Figueroa-Vargas, Alejandra, Góngora, Begoña, Alonso, María Francisca, Ortega, Alonso, Soto-Fernández, Patricio, Z-Rivera, Lucía, Ramírez, Sebastián, González, Francisca, Muñoz Venturelli, Paula, and Billeke, Pablo

Published
2024
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19. The RSNA Cervical Spine Fracture CT Dataset.

Author

Ball, Robyn, Gumeler, Ekim, Yeom, Kristen, Hamghalam, Mohammad, Simpson, Amber, Strika, Jasna, Bulja, Deniz, Angkurawaranon, Salita, Pérez-Lara, Almudena, Gómez-Alonso, María, Ortiz Jiménez, Johanna, Peoples, Jacob, Law, Meng, Dogan, Hakan, Altinmakas, Emre, Youssef, Ayda, Mahfouz, Yasser, Kalpathy-Cramer, Jayashree, Flanders, Adam, Lin, Hui, Colak, Errol, Richards, Tyler, Kitamura, Felipe, Prevedello, Luciano, and Talbott, Jason

Subjects
CT, Diagnosis, Feature Detection, Head/Neck, Informatics, Segmentation, Spine
Abstract

This dataset is composed of cervical spine CT images with annotations related to fractures; it is available at https://www.kaggle.com/competitions/rsna-2022-cervical-spine-fracture-detection/.

Published
2023

22. Are Young Female Basketball Players Adequately Prepared for a Force–Velocity Jumping and Sprinting Assessment?

Author

Rial-Vázquez, Jessica, Nine, Iván, Rúa-Alonso, María, Fariñas, Juan, Fernández-Seoane, Roberto, Jiménez-Reyes, Pedro, Fernández-del-Olmo, Miguel, and Iglesias-Soler, Eliseo

Subjects
BIOMECHANICS, MOTOR ability, RESEARCH funding, ACCELERATION (Mechanics), PHYSICAL training & conditioning, DESCRIPTIVE statistics, BASKETBALL, ATHLETIC ability, JUMPING, BODY movement, SPRINTING, RELIABILITY (Personality trait), PHYSIOLOGICAL effects of acceleration
Abstract

Purpose: The aim of this study was to explore the interday reliability of mechanical variables obtained from the horizontal and vertical force–velocity (FV) profiles in adolescent female basketball players. If found to be reliable, the associations between FV parameters (theoretical maximal force, velocity, and power), squat jump (SJ) height, 30-m sprint, and change of direction (COD) times were evaluated. Methods: After familiarization, SJ against incremental loads, 30-m sprint, and 505-COD tests were obtained twice in 36 adolescent female basketball players (age = 15.4 [1.2] y). Results: Reliability for vertical FV parameters was unacceptable, whereas 505-COD times and FV horizontal parameters (except for theoretical maximal power) showed a moderate to high reliability. 505-COD time was correlated with FV horizontal parameters (range: r = −.821, −.451), and a large association was observed with both SJ height (r = −.678, −.600) and 30-m sprint time (r =.813,.858). Conclusions: Due to low levels of strength, our athletes were not adequately prepared to obtain a reliable vertical FV profile. Practitioners can expect acceptable reliability of the horizontal FV profile. Given the association between COD performance and SJ height and 30-m sprint time, we encouraged practitioners with limited equipment at their disposal to use COD and/or 30-m sprint tests. [ABSTRACT FROM AUTHOR]

Published
2024
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41. Combining loop with thiazide diuretics in patients discharged home after a heart failure decompensation: Association with 30-day outcomes

Author

Fuentes, Marta, Davila, Aitor, del Amo, Sonia, Alonso, Héctor, Pérez-Llantada, Enrique, Martín-Sánchez, Francisco Javier, Miró, Òscar, Gil, Víctor, Escoda, Rosa, Sánchez, Carolina, Repullo, Daniel, Masso, Marta, Millán, Javier, Serrano, Leticia, Pavón, José, González, Nayra Cabrera, Rodríguez, Rafael Calvo, Reyes, Juan Antonio Vega, López-Grima, María Luisa, Valero, Amparo, Juan, María Ángeles, Aguirre, Alfons, Masó, Silvia Mínguez, Alonso, María Isabel, Mecina, Ana Belén, Tost, Josep, Ramón, Susana Sánchez, Rodríguez, Virginia Carbajosa, Piñera, Pascual, Nicolás, José Andrés Sánchez, Aragüés, Paula Lázaro, Garate, Raquel Torres, Rodríguez, Esther Álvarez, Arias, Pilar Paz, Alquézar-Arbé, Aitor, Herrera, Sergio, Carrete, Carlos José Romero, Jacob, Javier, Roset, Alex, Cabello, Irene, Haro, Antonio, Richard, Fernando, Fernández, Elisa, Diez, María Pilar López, Puente, Pablo Herrero, Álvarez, Joaquín Vázquez, García, Belén Prieto, Fernández, Alejandra Fernández, Ramos, Belén Álvarez, Miranda, Natalia Fernández, Llorens, Pere, Espinosa, Begoña, Jara, Gema, Felipe, Alba, Andueza, Juan Antonio, Romero, Rodolfo, López, Mariella Luengo, Domínguez, Gema, Ruíz, Martín, Arriaga, Beatriz Amores, Bergua, Beatriz Sierra, Mojarro, Enrique Martín, Jiménez, Lidia Cuevas, Bécquer, Lisette Travería, Burillo, Guillermo, García, Lluís Llauger, Urbano, Carmen Agüera, de los Ángeles, María, de la Torre, González, Jiménez, Carmen Esmeralda Romero, Ferrer, Ester Soy, Múñoz, María Adroher, Garrido, José Manuel, Lucas-Imbernón, Francisco Javier, Gaya, Rut, Bibiano, Carlos, Mir, María, Rodríguez, Beatriz, Martín, Monika Vicente, Adrada, Esther Rodríguez, Domingo, Eva, Carvajal, Marianela Guzmán, Fortuny, María José, García, Yelenis Gómez, de las Nieves Segura Coronill, Verónica, Esquivias, Marco Antonio, García, Rocío Moyano, Rodríguez, Pablo, Noceda, José, Blasco, Santiago Harris, Romero, Marta, Lorenzo, Miguel, Núñez, Gonzalo, de la Espriella, Rafael, Villar, Sandra, Santas, Enrique, Miñana, Gema, Bodí, Vicent, Sanchis, Juan, Núñez, Julio, Bautista, Prado Salamanca, Hueso, Rocío Ruiz, Domingo, Soraya, Núñez, Mª Victoria, Olmedo, Jesús, Vázquez, Carmen, López, Juan Bosco, Peinado, Alejandro, Montes, Juan Antonio, Díez-Manglano, Jesús, Rodés, Pablo Martínez, Garcés, Vanesa, Rubio, Jorge, Rodríguez, José M Fernández, Curto, Adrián Argüelles, Murphy, Orla Torrallardona, Manso, Meritxell Gavà, Martel, Alicia Conde, García, José Mª, González, Sonia, Dávila, Melitón F, Hernández, Rubén, Gudiño, Diego José, Mendoza, Humberto, Carrera, Margarita, Trullàs, Joan Carles, Epelde, Francisco, Biosca, Anna Sánchez, Becerra, Raquel, Gil, Mercè, Massi, Paulina Ivanova, Chivite, David, Formiga, Francesc, Núñez, Raquel, Pacho, Cristina, Contra, Anna, Ceresuela, Luis, Morales, José Luís, Pla, Xavi, López, Gabriel, Blázquez, Julio, Reboiro, Manuel Lorenzo López, Castro, José López, Asenjo, María, de Peralta, Paula, Llàcer, Pau, Manzano, Luis, Ortega, Raúl Antonio Ruiz, Vázquez, Miguel Ángel, Soler, Llanos, Mesado, Daniel, Casado, Jesús, Abad, Daniel, Ballesta, Ana Isabel Peláez, Rodríguez, Elena Morcillo, Lopez-Ayala, Pedro, Llauger, Lluís, Mollar, Anna, Garcés-Horna, Vanesa, Martínez-Nadal, Gemma, and Mueller, Christian

Published
2024
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