
- RIUMA Principal
- Investigación
- Listar Investigación por autor
Listar Investigación por autor "Urda, Daniel"
Mostrando ítems 1-3 de 3
-
Classification of high dimensional data using LASSO ensembles
The estimation of multivariable predictors with good performance in high dimensional settings is a crucial task in biomedical contexts. Usually, solutions based on the application of a single machine ... -
Deep Learning to Analyze RNA-Seq Gene Expression Data
Urda, Daniel; Montes-Torres, Julio; Moreno, Fernando; Franco, Leonardo
; Jerez-Aragonés, José Manuel
(Springer, 2017)
Deep learning models are currently being applied in several areas with great success. However, their application for the analysis of high-throughput sequencing data remains a challenge for the research community due to ... -
Machine learning models to search relevant genetic signatures in clinical context
Urda, Daniel; Luque-Baena, Rafael Marcos; Franco, Leonardo
; Sánchez-Maroño, Noelia; Jerez-Aragonés, José Manuel
(2017-06-26)
Clinicians are interested in the estimation of robust and relevant genetic signatures from gene sequencing data. Many machine learning approaches have been proposed trying to address well-known issues of this complex ...