Link to Source: web-based live tool
Authors:Giovanni Baj; Nicola Ciocca; Pooya Mohammadi Kazaj; Xuan Ma, Annina A Studer Bruengger; Simon F. Stämpfli; Niklas F Ehl; Sarah Hugelshofer; Otmar Pfister; Joëlle Lehmann; Christoph Ryffel; Lukas Hunziker; Michael Poledniczek; Andreas Kammerlander; George CM Siontis; Stephan Windecker; Moritz J. Hundertmark; Christian Nitsche; Isaac Shiri; Christoph Gräni
Summary: AiTTRIX is an explainable machine learning platform for individualised prognosis in transthyretin amyloid cardiomyopathy, estimating each patient’s risk of major adverse cardiovascular events to support transparent, data-driven stratification, and validated across multiple centres in Switzerland and an independent cohort in Vienna.
AiTTRIX (pronounced “A-trix”), Artificial Intelligence for TransThyretin cardiac amyloidosis RIsk prediction using an eXplainable model, is a clinical decision support platform for individualized prognostic assessment in ATTR-CM. It leverages machine learning to estimate the risk of major adverse cardiovascular events (MACE), enabling transparent and data-driven patient stratification.
AiTTRIX was developed using a Bern, Switzerland, cohort and externally validated across five centers in Switzerland, as well as an independent Vienna, Austria, cohort. AiTTRIX outperformed conventional risk scores and demonstrated strong generalizability across diverse populations.
Machine Learning–Driven Risk Prediction Model for Major Adverse Cardiovascular Events in Transthyretin Amyloid Cardiomyopathy: A Multicenter Study Development and Testing. Giovanni Baj; Nicola Ciocca; Pooya Mohammadi Kazaj; Xuan Ma, Annina A Studer Bruengger; Simon F. Stämpfli; Niklas F Ehl; Sarah Hugelshofer; Otmar Pfister; Joëlle Lehmann; Christoph Ryffel; Lukas Hunziker; Michael Poledniczek; Andreas Kammerlander; George CM Siontis; Stephan Windecker; Moritz J. Hundertmark; Christian Nitsche; Isaac Shiri; Christoph Gräni; Under Review, 2026.