Luongo, G., Azzolin, L., Schuler, S., Rivolta, M. W., Almeida, T. P., Martínez, J. P., Soriano, D. C., Luik, A., Müller-Edenborn, B., Jadidi, A. S., Dössel, O., Sassi, R., Laguna, P., & Loewe, A. [ca. 2021]. Machine learning enables noninvasive prediction of atrial fibrillation driver location and acute pulmonary vein ablation success using the 12-lead ECG [Cd]. Freiburg: Universität. https://doi.org/10.1016/j.cvdhj.2021.03.002

LUONGO, Giorgio, AZZOLIN, Luca, SCHULER, Steffen, RIVOLTA, Massimo W., ALMEIDA, Tiago P., MARTÍNEZ, Juan P., SORIANO, Diogo C., LUIK, Armin, MÜLLER-EDENBORN, Björn, JADIDI, Amir S., DÖSSEL, Olaf, SASSI, Roberto, LAGUNA, Pablo und LOEWE, Axel, 2021. Machine learning enables noninvasive prediction of atrial fibrillation driver location and acute pulmonary vein ablation success using the 12-lead ECG. Freiburg: Universität.

Luongo, G., L. Azzolin, S. Schuler, M. W. Rivolta, T. P. Almeida, J. P. Martínez, D. C. Soriano, A. Luik, B. Müller-Edenborn, A. S. Jadidi, O. Dössel, R. Sassi, P. Laguna, und A. Loewe. Machine learning enables noninvasive prediction of atrial fibrillation driver location and acute pulmonary vein ablation success using the 12-lead ECG. cd, Universität, 2021, https://doi.org/10.1016/j.cvdhj.2021.03.002.

Luongo, Giorgio/Azzolin, Luca/Schuler, Steffen/Rivolta, Massimo W./Almeida, Tiago P./Martínez, Juan P. u. a.: Machine learning enables noninvasive prediction of atrial fibrillation driver location and acute pulmonary vein ablation success using the 12-lead ECG, Freiburg 2021.

Luongo, G., Azzolin, L., Schuler, S., Rivolta, M.W., Almeida, T.P., Martínez, J.P., Soriano, D.C., Luik, A., Müller-Edenborn, B., Jadidi, A.S., Dössel, O., Sassi, R., Laguna, P. und Loewe, A. (2021), Machine learning enables noninvasive prediction of atrial fibrillation driver location and acute pulmonary vein ablation success using the 12-lead ECG, Bd. , Universität, Freiburg, verfügbar unter:https://doi.org/10.1016/j.cvdhj.2021.03.002.