Simplified Outcome Prediction in Patients Undergoing Transcatheter Tricuspid Valve Intervention by Survival Tree-Based Modelling

Authors: Vera Fortmeier, MD, Mark Lachmann, MD, Lukas Stolz, MD, Jennifer von Stein, MD, Karl-Philipp Rommel, MD, Mohammad Kassar, MD, Muhammed Gerçek, MD, Anne R. Schöber, MD, Thomas J. Stocker, MD, Hazem Omran, MD, Michelle Fett, Jule Tervooren, Maria I. Körber, MD, Amelie Hesse, Gerhard Harmsen, PhD, Kai Peter Friedrichs, MD, Shinsuke Yuasa, MD, PhD, Tanja K. Rudolph, MD, Michael Joner, MD, Roman Pfister, MD, Stephan Baldus, MD, Karl-Ludwig Laugwitz, MD, Stephan Windecker, MD, Fabien Praz, MD, Philipp Lurz, MD, Jörg Hausleiter, MD, Volker Rudolph, MD

Source: JACC: Advances, Vol 4, Iss 2, Pp 101575- (2025)

Subject Terms: machine learning, transcatheter tricuspid valve intervention, tricuspid regurgitation, Diseases of the circulatory (Cardiovascular) system, RC666-701, Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9

File Description: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2772963X24008561; https://doaj.org/toc/2772-963X

Access URL: https://doaj.org/article/2f1e5d3fc4694f26902a39bd1b1e9f98