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Application of Machine Learning to improve the efficiency of electrophysiological simulations used for the prediction of drug-induced ventricular arrhythmia

Rodriguez-Belenguer, Pablo; Kopanska, Karolina; Llopis-Lorente, Jordi; Trenor Gomis, Beatriz Ana; Saiz Rodríguez, Francisco Javier; Pastor, Manuel (Elsevier, 2023-03)

[EN] Background and Objective In silico prediction of drug-induced ventricular arrhythmia often requires computationally intensive simulations, making its application tedious and non-interactive. This inconvenience can ...
Uncertainty assessment of proarrhythmia predictions derived from multi-level in silico models

Kopanska, Karolina; Rodriguez-Belenguer, Pablo; Llopis-Lorente, Jordi; Trenor Gomis, Beatriz Ana; Saiz Rodríguez, Francisco Javier; Pastor, Manuel (Springer-Verlag, 2023-08-01)

[EN] In silico methods can be used for an early assessment of arrhythmogenic properties of drug candidates. However, their use for decision-making is conditioned by the possibility to estimate the predictions' uncertainty. ...

Mostrando ítems 1-2 de 2