Alfredo Vellido
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| Ungan G, Pons-Escoda A, Ulinic D, et al. (2024) Early pseudoprogression and progression lesions in glioblastoma patients are both metabolically heterogeneous. Nmr in Biomedicine. e5095 |
| Hernández-Villegas Y, Ortega-Martorell S, Arús C, et al. (2019) Extraction of artefactual MRS patterns from a large database using non-negative matrix factorization. Nmr in Biomedicine. e4193 |
| Vellido A. (2019) The importance of interpretability and visualization in machine learning for applications in medicine and health care Neural Computing and Applications. 1-15 |
| König C, Shaim I, Vellido A, et al. (2018) Using machine learning tools for protein database biocuration assistance. Scientific Reports. 8: 10148 |
| Lisboa PJG, Martín-Guerrero JD, Vellido A. (2015) Making nonlinear manifold learning models interpretable: The manifold grand tour Expert Systems With Applications. 42: 8982-8988 |
| Arizmendi C, Sierra DA, Vellido A, et al. (2014) Automated classification of brain tumours from short echo time in vivo MRS data using Gaussian Decomposition and Bayesian Neural Networks Expert Systems With Applications. 41: 5296-5307 |
| Tosi A, Olier I, Vellido A. (2014) Probability Ridges and Distortion Flows: Visualizing Multivariate Time Series Using a Variational Bayesian Manifold Learning Method Advances in Intelligent Systems and Computing. 295: 55-64 |
| Ortega-Martorell S, Ruiz H, Vellido A, et al. (2013) A novel semi-supervised methodology for extracting tumor type-specific MRS sources in human brain data. Plos One. 8: e83773 |
| Cruz-Barbosa R, Vellido A. (2013) Generative manifold learning for the exploration of partially labeled data Computacion Y Sistemas. 17: 641-653 |
| Vilamala A, Lisboa PJG, Ortega-Martorell S, et al. (2013) Discriminant Convex Non-negative Matrix Factorization for the classification of human brain tumours Pattern Recognition Letters. 34: 1734-1747 |