Development and validation of explainable machine learning models for risk of mortality in transcatheter aortic valve implantation: TAVI risk machine scores.

Andreas Leha Cynthia Huber Tim FriedeTimm BauerAndreas BeckmannRaffi Bekeredjian Sabine Bleiziffer Eva HerrmannHelge MöllmannThomas Walther Friedhelm BeyersdorfChristian HammArnaud Künzi Stephan Windecker Stefan Stortecky Ingo Kutschka Gerd Hasenfuss Stephan EnsmingerChristian FrerkerTim Seidler

Published in: European heart journal. Digital health (2023)

TRIM scores demonstrate good performance for risk estimation before and after TAVI. Together with clinical judgement, they may support standardised and objective decision-making before and after TAVI.

Keyphrases

transcatheter aortic valve implantation
aortic valve
aortic valve replacement
aortic stenosis
machine learning
transcatheter aortic valve replacement
decision making
deep learning
cardiovascular events
left ventricular
artificial intelligence
risk factors
type diabetes
heart failure
big data