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Physiology-based regularization of the electrocardiographic inverse problem., , , , , and . Medical Biol. Eng. Comput., 55 (8): 1353-1365 (2017)Determinants of Beat-to-Beat Variability of Repolarization Duration in the Canine Ventricular Myocyte: A Computational Analysis., , , , , , and . PLoS Comput. Biol., (2013)Hydropathicity-based prediction of pain-causing NaV1.7 variants., , , , , , , , , and 1 other author(s). BMC Bioinform., 22 (1): 212 (2021)Multiwavelet Design for Cardiac Signal Processing., , , , and . EMBC, page 1682-1685. IEEE, (2006)Physiology-based Regularization Improves Noninvasive Reconstruction and Localization of Cardiac Electrical Activity., , , , and . CinC, page 1-4. www.cinc.org, (2014)Inverse Reconstruction of Epicardial Potentials Improves by Vectorcardiography and Realistic Potentials., , , , , and . CinC, page 369-372. www.cinc.org, (2013)Realistic training data improve noninvasive reconstruction of heart-surface potentials., , , and . EMBC, page 6373-6376. IEEE, (2012)In-vivo Evaluation of Reduced-Lead-Systems in Noninvasive Reconstruction and Localization of Cardiac Electrical Activity., , , , , , and . CinC, page 221-224. www.cinc.org, (2015)An L2-based approach for wavelet approximation., , , , and . CDC/ECC, page 7882-7887. IEEE, (2005)The Identification of Dynamic Gene-Protein Networks., , , , and . KDECB, volume 4366 of Lecture Notes in Computer Science, page 157-170. Springer, (2006)