Machine Learning–Driven Risk Prediction Model in Transthyretin Amyloid Cardiomyopathy
JAMA Cardiology 10.1001/jamacardio.2026.3496August 28, 2026 at 7:45 AM EDT
An ML-based time-to-event prediction model demonstrated promising predictive performance and showed improved discrimination compared with established staging systems in patients with ATTR-CM, supporting its potential for individualized prognostication.
Meeting Information: ESC 2026
This paper will be presented during European Society of Cardiology Congress in Munich, Germany.
Local Embargo Time: 13:45 (1:45 P.M.) CEST.
ESC Presentation: The paper will be featured during the Symposium “How imaging-based digital twins, artificial intelligence, and robotics will guide interventions” on the Digital Health Stage.
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