Zobrazeno 1 - 10
of 323
pro vyhledávání: '"Rios, Miguel A."'
Autor:
Rios, Miguel
Large Language Models (LLMs) have shown promising results on machine translation for high resource language pairs and domains. However, in specialised domains (e.g. medical) LLMs have shown lower performance compared to standard neural machine transl
Externí odkaz:
http://arxiv.org/abs/2408.16440
Autor:
Domínguez-Ríos, Miguel Ángel, Chicano, Francisco, Alba, Enrique, del Águila, Isabel María, del Sagrado, José
Publikováno v:
J. Sys. Soft. 156: 217-231 (2019)
The Next Release Problem consists in selecting a subset of requirements to develop in the next release of a software product. The selection should be done in a way that maximizes the satisfaction of the stakeholders while the development cost is mini
Externí odkaz:
http://arxiv.org/abs/2402.04586
Publikováno v:
Inf. Sci. 565: 210-228 (2021)
In multiobjective optimization, the result of an optimization algorithm is a set of efficient solutions from which the decision maker selects one. It is common that not all the efficient solutions can be computed in a short time and the search algori
Externí odkaz:
http://arxiv.org/abs/2403.08807
Autor:
Blanco-Rios, Miguel A., Candela-Leal, Milton O., Orozco-Romo, Cecilia, Remis-Serna, Paulina, Velez-Saboya, Carol S., Lozoya-Santos, Jorge De-J., Cebral-Loureda, Manuel, Ramirez-Moreno, Mauricio A.
Publikováno v:
Frontiers in Human Neuroscience, 18, 1319574 (2024)
Within the field of Humanities, there is a recognized need for educational innovation, as there are currently no reported tools available that enable individuals to interact with their environment to create an enhanced learning experience in the huma
Externí odkaz:
http://arxiv.org/abs/2401.15743
Autor:
Rios, Miguel, Abu-Hanna, Ameen
Intensive Care in-hospital mortality prediction has various clinical applications. Neural prediction models, especially when capitalising on clinical notes, have been put forward as improvement on currently existing models. However, to be acceptable
Externí odkaz:
http://arxiv.org/abs/2212.06267
Multilingual Neural Machine Translation (MNMT) models leverage many language pairs during training to improve translation quality for low-resource languages by transferring knowledge from high-resource languages. We study the quality of a domain-adap
Externí odkaz:
http://arxiv.org/abs/2212.02143
Autor:
Rios, Miguel, Abu-Hanna, Ameen
Neural models, with their ability to provide novel representations, have shown promising results in prediction tasks in healthcare. However, patient demographics, medical technology, and quality of care change over time. This often leads to drop in t
Externí odkaz:
http://arxiv.org/abs/2212.00557
Autor:
Gil-Rios, Miguel-Angel1 (AUTHOR) mgil@utleon.edu.mx, Cruz-Aceves, Ivan2 (AUTHOR) ivan.cruz@cimat.mx, Hernandez-Aguirre, Arturo3 (AUTHOR) artha@cimat.mx, Hernandez-Gonzalez, Martha-Alicia4 (AUTHOR) martha.hernandez@imss.gob.mx, Solorio-Meza, Sergio-Eduardo5 (AUTHOR) se.solorio@ugto.mx
Publikováno v:
Diagnostics (2075-4418). Nov2024, Vol. 14 Issue 21, p2372. 19p.
Autor:
Jimenez Rios, Miguel Angel1 (AUTHOR) incanurologia@gmail.com, Scavuzzo, Anna1 (AUTHOR) annasc80@gmail.com, Noverón, Nancy Reynoso2 (AUTHOR) reynonove1@gmail.com, García Arango, Caleb2 (AUTHOR) caleb.garc@gmail.com, Calvo Vazquez, Ivan1 (AUTHOR), Hurtado Vázquez, Alonso3 (AUTHOR), Arrieta Rodriguez, Oscar Gerardo4 (AUTHOR), Davila, Miguel Angel Jimenez1 (AUTHOR), Sighinolfi, Maria Chiara5,6 (AUTHOR) bernardo.rocco@gmail.com, Rocco, Bernardo6 (AUTHOR)
Publikováno v:
Cancers. Nov2024, Vol. 16 Issue 21, p3675. 13p.
Negation detection in Dutch clinical texts: an evaluation of rule-based and machine learning methods
Autor:
van Es, Bram, Reteig, Leon C., Tan, Sander C., Schraagen, Marijn, Hemker, Myrthe M., Arends, Sebastiaan R. S., Rios, Miguel A. R., Haitjema, Saskia
As structured data are often insufficient, labels need to be extracted from free text in electronic health records when developing models for clinical information retrieval and decision support systems. One of the most important contextual properties
Externí odkaz:
http://arxiv.org/abs/2209.00470