Publicacións en colaboración con investigadores/as de Universitat Pompeu Fabra (62)

2024

  1. A machine learning approach to identify groups of patients with hematological malignant disorders

    Computer Methods and Programs in Biomedicine, Vol. 246

  2. Automatic and interpretable prediction of the site of origin in outflow tract ventricular arrhythmias: machine learning integrating electrocardiograms and clinical data

    Frontiers in Cardiovascular Medicine, Vol. 11

  3. Integrating Mechanistic and Toxicokinetic Information in Predictive Models of Cholestasis

    Journal of Chemical Information and Modeling, Vol. 64, Núm. 7, pp. 2775-2788

  4. Patient Stratification Based on Fast Simulation of Cardiac Electrophysiology on Digital Twins

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2023

  1. Analysis of Non-imaging Data

    AI and Big Data in Cardiology: a Practical Guide (Springer International Publishing), pp. 183-200

  2. Automatic Prediction of the Origin in Outflow Tract Ventricular Arrhythmias with Machine Learning Combining Clinical Data and Electrocardiogram Analysis

    Computing in Cardiology

  3. Client Applications and Server-Side Docker for Management of RNASeq and/or VariantSeq Workflows and Pipelines of the GPRO Suite

    Genes, Vol. 14, Núm. 2

  4. Usage of model combination in computational toxicology

    Toxicology Letters, Vol. 389, pp. 34-44

2022

  1. Applicability of probabilistic graphical models for early detection of SARS-CoV-2 reactive antibodies after SARS-CoV-2 vaccination in hematological patients

    Annals of Hematology, Vol. 101, Núm. 9, pp. 2053-2067

  2. Meshless Electrophysiological Modeling of Cardiac Resynchronization Therapy—Benchmark Analysis with Finite-Element Methods in Experimental Data

    Applied Sciences (Switzerland), Vol. 12, Núm. 13

  3. Personalized Fast Electrophysiology Simulations to Evaluate Arrhythmogenicity of Ventricular Slow Conduction Channels

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  4. Training machine learning models with synthetic data improves the prediction of ventricular origin in outflow tract ventricular arrhythmias

    Frontiers in Physiology, Vol. 13

2021

  1. Cardiac computational modelling

    Revista Espanola de Cardiologia, Vol. 74, Núm. 1, pp. 65-71

  2. The relationship between resistance exercise performance and ventilatory efficiency after beetroot juice intake in well-trained athletes

    Nutrients, Vol. 13, Núm. 4

2020

  1. Cadmium, smoking, and human blood DNA methylation profiles in adults from the strong heart study

    Environmental Health Perspectives, Vol. 128, Núm. 6

  2. In silico pace-mapping: Prediction of left vs. right outflow tract origin in idiopathic ventricular arrhythmias with patient-specific electrophysiological simulations

    Europace, Vol. 22, Núm. 9, pp. 1419-1430

  3. Reverse-Transcribing Viruses (Belpaoviridae, Metaviridae, and Pseudoviridae)

    Encyclopedia of Virology: Volume 1-5, Fourth Edition (Elsevier), pp. 653-666

  4. Understanding the effects of beetroot juice intake on CrossFit performance by assessing hormonal, metabolic and mechanical response: a randomized, double-blind, crossover design

    Journal of the International Society of Sports Nutrition, Vol. 17, Núm. 1

2019

  1. A rule-based method to model myocardial fiber orientation in cardiac biventricular geometries with outflow tracts

    International Journal for Numerical Methods in Biomedical Engineering, Vol. 35, Núm. 4

  2. Predicting the Origin of Outflow Tract Ventricular Arrhythmias Using Machine Learning Techniques Trained with Patient-Specific Electrophysiological Simulations

    Computing in Cardiology