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Page 1
Deep Learning-Enabled Assessment of Right Ventricular Function Improves Prognostication After Transcatheter Edge-to-Edge Repair for Mitral Regurgitation.
Lachmann M, Fortmeier V, Stolz L, Tokodi M, Kovács A, Hesse A, Leipert A, Rippen E, Alvarez Covarrubias HA, von Scheidt M, Tervooren J, Roski F, Fett M, Gerçek M, Schuster T, Harmsen G, Yuasa S, Mayr NP, Kastrati A, Schunkert H, Joner M, Xhepa E, Laugwitz KL, Hausleiter J, Rudolph V, Trenkwalder T. Lachmann M, et al. Among authors: rippen e. Circ Cardiovasc Imaging. 2025 Jan;18(1):e017005. doi: 10.1161/CIRCIMAGING.124.017005. Epub 2025 Jan 21. Circ Cardiovasc Imaging. 2025. PMID: 39836730
Invasive Assessment of Right Ventricular to Pulmonary Artery Coupling Improves 1-year Mortality Prediction After Transcatheter Aortic Valve Replacement and Anticipates the Persistence of Extra-Aortic Valve Cardiac Damage.
Lachmann M, Hesse A, Trenkwalder T, Xhepa E, Rheude T, von Scheidt M, Covarrubias HAA, Rippen E, Hramiak O, Pellegrini C, Schuster T, Yuasa S, Schunkert H, Kastrati A, Kupatt C, Laugwitz KL, Joner M. Lachmann M, et al. Among authors: rippen e. Struct Heart. 2024 Mar 15;8(3):100282. doi: 10.1016/j.shj.2024.100282. eCollection 2024 May. Struct Heart. 2024. PMID: 38799808 Free PMC article.
Machine learning identifies pathophysiologically and prognostically informative phenotypes among patients with mitral regurgitation undergoing transcatheter edge-to-edge repair.
Trenkwalder T, Lachmann M, Stolz L, Fortmeier V, Covarrubias HAA, Rippen E, Schürmann F, Presch A, von Scheidt M, Ruff C, Hesse A, Gerçek M, Mayr NP, Ott I, Schuster T, Harmsen G, Yuasa S, Kufner S, Hoppmann P, Kupatt C, Schunkert H, Kastrati A, Laugwitz KL, Rudolph V, Joner M, Hausleiter J, Xhepa E. Trenkwalder T, et al. Among authors: rippen e. Eur Heart J Cardiovasc Imaging. 2023 Apr 24;24(5):574-587. doi: 10.1093/ehjci/jead013. Eur Heart J Cardiovasc Imaging. 2023. PMID: 36735333
Harnessing feature extraction capacities from a pre-trained convolutional neural network (VGG-16) for the unsupervised distinction of aortic outflow velocity profiles in patients with severe aortic stenosis.
Lachmann M, Rippen E, Rueckert D, Schuster T, Xhepa E, von Scheidt M, Pellegrini C, Trenkwalder T, Rheude T, Stundl A, Thalmann R, Harmsen G, Yuasa S, Schunkert H, Kastrati A, Joner M, Kupatt C, Laugwitz KL. Lachmann M, et al. Among authors: rippen e. Eur Heart J Digit Health. 2022 Apr 22;3(2):153-168. doi: 10.1093/ehjdh/ztac004. eCollection 2022 Jun. Eur Heart J Digit Health. 2022. PMID: 36713009 Free PMC article.
Artificial intelligence-enabled phenotyping of patients with severe aortic stenosis: on the recovery of extra-aortic valve cardiac damage after transcatheter aortic valve replacement.
Lachmann M, Rippen E, Schuster T, Xhepa E, von Scheidt M, Trenkwalder T, Pellegrini C, Rheude T, Hesse A, Stundl A, Harmsen G, Yuasa S, Schunkert H, Kastrati A, Laugwitz KL, Joner M, Kupatt C. Lachmann M, et al. Among authors: rippen e. Open Heart. 2022 Oct;9(2):e002068. doi: 10.1136/openhrt-2022-002068. Open Heart. 2022. PMID: 36261218 Free PMC article.
Solving the Pulmonary Hypertension Paradox in Patients With Severe Tricuspid Regurgitation by Employing Artificial Intelligence.
Fortmeier V, Lachmann M, Körber MI, Unterhuber M, von Scheidt M, Rippen E, Harmsen G, Gerçek M, Friedrichs KP, Roder F, Rudolph TK, Yuasa S, Joner M, Laugwitz KL, Baldus S, Pfister R, Lurz P, Rudolph V. Fortmeier V, et al. Among authors: rippen e. JACC Cardiovasc Interv. 2022 Feb 28;15(4):381-394. doi: 10.1016/j.jcin.2021.12.043. JACC Cardiovasc Interv. 2022. PMID: 35210045 Free article.
Subphenotyping of Patients With Aortic Stenosis by Unsupervised Agglomerative Clustering of Echocardiographic and Hemodynamic Data.
Lachmann M, Rippen E, Schuster T, Xhepa E, von Scheidt M, Pellegrini C, Trenkwalder T, Rheude T, Stundl A, Thalmann R, Harmsen G, Yuasa S, Schunkert H, Kastrati A, Laugwitz KL, Kupatt C, Joner M. Lachmann M, et al. Among authors: rippen e. JACC Cardiovasc Interv. 2021 Oct 11;14(19):2127-2140. doi: 10.1016/j.jcin.2021.08.034. JACC Cardiovasc Interv. 2021. PMID: 34620391 Free article.