Artificial intelligence-enabled phenotyping of patients with severe aortic stenosis: on the recovery of extra-aortic valve cardiac damage after transcatheter aortic valve replaceme... by Lachmann, Mark, Rippen, Elena, Schuster, Tibor, Xhepa, Erion, von Scheidt, Moritz, Trenkwalder, Teresa, Pellegrini, Costanza, Rheude, Tobias, Hesse, Amelie, Stundl, Anja, Harmsen, Gerhard, Yuasa, Shinsuke, Schunkert, Heribert, Kastrati, Adnan, Laugwitz, Karl-Ludwig, Joner, Michael, Kupatt, Christian

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Abstract 9220: Employing a Convolutional Neural Network Facilitates Unsupervised Clustering of Aortic Outflow Velocity Profiles from Patients With Severe Aortic Stenosis by Lachmann, Mark, Rippen, Elena, Harmsen, Gerhard, Xhepa, Erion, Rueckert, Daniel

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TCT-496 Artificial Intelligence-Enabled Phenotyping of Patients with Severe Mitral Regurgitation: on the Recovery of Extra-Mitral Valve Cardiac Damage after Transcatheter Edge-to-E... by Rippen, Elena, Lachmann, Mark, Trenkwalder, Teresa, Schuster, Tibor, Xhepa, Erion, von Scheidt, Moritz, Harmsen, Gerhard, Yuasa, Shinsuke, Kupatt, Christian, Joner, Michael, Laugwitz, Karl-Ludwig

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TCT-162 Unsupervised Clustering Based on Routine Structural and Functional Echocardiography Parameters Identifies 4 Pathophysiologically and Prognostically Informative Phenotypes A... by Rippen, Elena, Lachmann, Mark, Trenkwalder, Teresa, Covarrubias, Hector Alvarez, Stolz, Lukas, Fortmeier, Vera, Gerçek, Muhammed, Kupatt, Christian, Laugwitz, Karl-Ludwig, Joner, Michael, Hausleiter, Jörg, Rudolph, Volker, Xhepa, Erion

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Subphenotyping of Patients With Aortic Stenosis by Unsupervised Agglomerative Clustering of Echocardiographic and Hemodynamic Data by Lachmann, Mark, Rippen, Elena, Schuster, Tibor, Xhepa, Erion, von Scheidt, Moritz, Pellegrini, Costanza, Trenkwalder, Teresa, Rheude, Tobias, Stundl, Anja, Thalmann, Ruth, Harmsen, Gerhard, Yuasa, Shinsuke, Schunkert, Heribert, Kastrati, Adnan, Laugwitz, Karl-Ludwig, Kupatt, Christian, Joner, Michael

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TCT-570 Deep Learning-Enabled Assessment of Right Ventricular Function Using 2D Echocardiograms Improves 1-Year Mortality Prediction in Patients With Severe Mitral Regurgitation Un... by Lachmann, Mark, Fortmeier, Vera, Tokodi, Marton, Harmsen, Gerhard, Covarrubias, Hector Alvarez, Gerçek, Muhammed, Rippen, Elena, Hesse, Amelie, Leipert, Antonia, von Scheidt, Moritz, Mayr, Patrick, Yuasa, Shinsuke, Xhepa, Erion, Joner, Michael, Laugwitz, Karl-Ludwig, Rudolph, Volker, Trenkwalder, Teresa

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TCT-409 Unsupervised Clustering of Structural and Functional Echocardiographic Parameters Identifies a High-Risk Phenotype Among Patients With Severe Mitral Regurgitation Undergoin... by Trenkwalder, Teresa, Lachmann, Mark, Covarrubias, Héctor Alvarez, Rippen, Elena, Schürmann, Friederike, Presch, Antonia, Ruff, Céline, von Scheidt, Moritz, Hoppmann, Petra, Kupatt, Christian, Mayr, Patrick, Schunkert, Heribert, Kastrati, Adnan, Joner, Michael, Xhepa, Erion

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Solving the Pulmonary Hypertension Paradox in Patients With Severe Tricuspid Regurgitation by Employing Artificial Intelligence by Fortmeier, Vera, Lachmann, Mark, Körber, Maria I., Unterhuber, Matthias, von Scheidt, Moritz, Rippen, Elena, Harmsen, Gerhard, Gerçek, Muhammed, Friedrichs, Kai Peter, Roder, Fabian, Rudolph, Tanja K., Yuasa, Shinsuke, Joner, Michael, Laugwitz, Karl-Ludwig, Baldus, Stephan, Pfister, Roman, Lurz, Philipp, Rudolph, Volker

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Machine learning identifies pathophysiologically and prognostically informative phenotypes among patients with mitral regurgitation undergoing transcatheter edge-to-edge repair by Trenkwalder, Teresa, Lachmann, Mark, Stolz, Lukas, Fortmeier, Vera, Covarrubias, Héctor Alfonso Alvarez, Rippen, Elena, Schürmann, Friederike, Presch, Antonia, von Scheidt, Moritz, Ruff, Celine, Hesse, Amelie, Gerçek, Muhammed, Mayr, N Patrick, Ott, Ilka, Schuster, Tibor, Harmsen, Gerhard, Yuasa, Shinsuke, Kufner, Sebastian, Hoppmann, Petra, Kupatt, Christian, Schunkert, Heribert, Kastrati, Adnan, Laugwitz, Karl-Ludwig, Rudolph, Volker, Joner, Michael, Hausleiter, Jörg, Xhepa, Erion

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Harnessing feature extraction capacities from a pre-trained convolutional neural network (VGG-16) for the unsupervised distinction of aortic outflow velocity profiles in patients w... by Lachmann, Mark, Rippen, Elena, Rueckert, Daniel, Schuster, Tibor, Xhepa, Erion, von Scheidt, Moritz, Pellegrini, Costanza, Trenkwalder, Teresa, Rheude, Tobias, Stundl, Anja, Thalmann, Ruth, Harmsen, Gerhard, Yuasa, Shinsuke, Schunkert, Heribert, Kastrati, Adnan, Joner, Michael, Kupatt, Christian, Laugwitz, Karl Ludwig

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Invasive Assessment of Right Ventricular to Pulmonary Artery Coupling Improves 1-year Mortality Prediction After Transcatheter Aortic Valve Replacement and Anticipates the Persiste... by Lachmann, Mark, Hesse, Amelie, Trenkwalder, Teresa, Xhepa, Erion, Rheude, Tobias, von Scheidt, Moritz, Covarrubias, Héctor Alfonso Alvarez, Rippen, Elena, Hramiak, Oksana, Pellegrini, Costanza, Schuster, Tibor, Yuasa, Shinsuke, Schunkert, Heribert, Kastrati, Adnan, Kupatt, Christian, Laugwitz, Karl-Ludwig, Joner, Michael

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