3 papers
Bayesian Integration of Nonlinear Incomplete Clinical Data
LucÃa González-Zamorano, Nuria Balbás-Esteban, Vanessa Gómez-Verdejo +2
Multimodal clinical data are characterized by high dimensionality, heterogeneous representations, and structured missingness, posing significant challenges for predictive modeling,…
Interpretable Generative and Discriminative Learning for Multimodal and Incomplete Clinical Data
Albert Belenguer-Llorens, Carlos Sevilla-Salcedo, Janaina Mourao-Miranda +1
Real-world clinical problems are often characterized by multimodal data, usually associated with incomplete views and limited sample sizes in their cohorts, posing significant limi…
Unified Bayesian representation for high-dimensional multi-modal biomedical data for small-sample classification
Albert Belenguer-Llorens, Carlos Sevilla-Salcedo, Jussi Tohka +1
We present BALDUR, a novel Bayesian algorithm designed to deal with multi-modal datasets and small sample sizes in high-dimensional settings while providing explainable solutions.…