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2020 – today
- 2023
[j4]Pablo Rodríguez-Belenguer
, Karolina Kopanska, Jordi Llopis-Lorente, Beatriz Trénor, Javier Saiz, Manuel Pastor:
Application of machine learning to improve the efficiency of electrophysiological simulations used for the prediction of drug-induced ventricular arrhythmia. Comput. Methods Programs Biomed. 230: 107345 (2023)- [j3]Jordi Llopis-Lorente, Samuel Baroudi, Kévin Koloskoff, Maria Teresa Mora, Matthieu Basset, Lucía Romero, Sylvain Benito, Frédéric Dayan, Javier Saiz, Beatriz Trénor:
Combining pharmacokinetic and electrophysiological models for early prediction of drug-induced arrhythmogenicity. Comput. Methods Programs Biomed. 242: 107860 (2023) - [c3]Safaa Al-Ali, Jordi Llopis-Lorente, Maria Teresa Mora, Maxime Sermesant, Beatriz Trénor, Irene Balelli:
A Causal Discovery Approach to Streamline Ionic Currents Selection to Improve Drug-Induced TdP Risk Assessment. CinC 2023: 1-4 - 2022
- [j2]Jordi Llopis-Lorente, Beatriz Trénor, Javier Saiz:
Considering population variability of electrophysiological models improves the in silico assessment of drug-induced torsadogenic risk. Comput. Methods Programs Biomed. 221: 106934 (2022) - [c2]Ilsbeth Gerarda Maria van Herck, Maria Teresa Mora, Jordi Llopis-Lorente, Henrik Nicolay Topnes Finsberg, Cécile Daversin-Catty, Javier Saiz, Beatriz Trénor, Hermenegild Arevalo, Samuel T. Wall:
Omecamtiv Mecarbil Improves Contraction Behaviour in a 3D Electromechanical Tissue Model of Heart Failure. CinC 2022: 1-4 - 2021
- [c1]Jordi Llopis-Lorente, Beatriz Trénor, Javier Saiz:
Prediction of Drug-Induced Arrhythmogenic Risk Using In Silico Populations of Models. CinC 2021: 1-4 - 2020
- [j1]Jordi Llopis-Lorente, Julio Gomis-Tena, Jordi Cano, Lucía Romero, Javier Saiz, Beatriz Trénor:
In Silico Classifiers for the Assessment of Drug Proarrhythmicity. J. Chem. Inf. Model. 60(10): 5172-5187 (2020)
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