2 citations · 4 across the 14 of their papers we have counts for
7 papers · 1 filter
Biologically Informed Representation Learning for Robust Cross-Center Generalization of MALDI-TOF Mass Spectrometry
Alejandro L. García-Navarro, Carlos Sevilla-Salcedo, Belén Rodríguez-Sánchez +1
Machine learning models for MALDI-TOF mass spectrometry have shown considerable promise for clinical microbiology tasks such as microbial identification and antimicrobial resistanc…
Bayesian Integration of Nonlinear Incomplete Clinical Data
Lucía 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,…
AI-driven Generation of MALDI-TOF MS for Microbial Characterization
Lucía Schmidt-Santiago, David Rodríguez-Temporal, Carlos Sevilla-Salcedo +1
Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) has become a cornerstone technology in clinical microbiology, enabling rapid and accurat…
Latent Representations of Intracardiac Electrograms for Atrial Fibrillation Driver Detection
Pablo Peiro-Corbacho, Long Lin, Pablo Ávila +4
Atrial Fibrillation (AF) is the most prevalent sustained arrhythmia, yet current ablation therapies, including pulmonary vein isolation, are frequently ineffective in persistent AF…
The Relevance Feature and Vector Machine for health applications
Albert Belenguer-Llorens, Carlos Sevilla-Salcedo, Emilio Parrado-Hernández +1
This paper presents the Relevance Feature and Vector Machine (RFVM), a novel model that addresses the challenges of the fat-data problem when dealing with clinical prospective stud…
Optimizing Feature Selection for Binary Classification with Noisy Labels: A Genetic Algorithm Approach
Vandad Imani, Elaheh Moradi, Carlos Sevilla-Salcedo +2
Feature selection in noisy label scenarios remains an understudied topic. We propose a novel genetic algorithm-based approach, the Noise-Aware Multi-Objective Feature Selection Gen…
Multimodal hierarchical Variational AutoEncoders with Factor Analysis latent space
Alejandro Guerrero-López, Carlos Sevilla-Salcedo, Vanessa Gómez-Verdejo +1
Purpose: Handling heterogeneous and mixed data types has become increasingly critical with the exponential growth in real-world databases. While deep generative models attempt to m…