A streamlined, machine learning-derived approach to risk-stratification in heart failure patients with secondary tricuspid regurgitation.

Gregor HeitzingerGeorg SpinkaSophia KoschatkoClemens BaumgartnerVarius DannenbergKseniya HalavinaKatharina MascherbauerChristian NitscheCaroliná DonaMatthias Koschutnik Andreas Anselm KammerlanderMax-Paul WinterGuido StrunkNoemi PavoStefan KastlMartin HülsmannRaphael RosenhekChristian Hengstenberg Philipp E Bartko Georg Goliasch

Published in: European heart journal. Cardiovascular Imaging (2023)

This study presents a streamlined, machine learning-derived and internally validated approach to risk-stratification in patients with moderate and severe sTR, that adds important prognostic information to aid clinical-decision-making.

Keyphrases

machine learning
heart failure
decision making
aortic valve
artificial intelligence
big data
aortic stenosis
mitral valve
deep learning
left ventricular
early onset
transcatheter aortic valve replacement
atrial fibrillation
coronary artery disease
social media