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Automated, transferable feature selection in risk models for heart failure patients using Iterative Hard Thresholding: a comparison across linear and nonlinear algorithms using routine care data

13 November 2026 (09:30 - 10:15)
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Congress Presentation Part of: Beyond the risk score Machine Learning Delegates Premium Access ESC Digital & AI Summit 2026 European Society of Cardiology

About the speaker

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Ms Mathilde Tans

Amsterdam University Medical Centre (AUMC), Amsterdam (Netherlands (The))

6 More presentations in this session

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PERISCOPE: a set of machine-learning models for predicting mortality in patients with STEMI following PCI
Doctor A. Rafanelli (Amsterdam, NL)
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Comparing machine learning and conventional risk scores for five-year CVD prediction in midlife women
Mr A. Cejudo (Donostia, ES)
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Unsupervised clustering of heart rate trajectories during exercise reveals 4 groups of patients with distinct cardiovascular profiles
Mr A. Rammal (Paris, FR)
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Memetic pattern-based algorithm improves prediction of major adverse cardiovascular events
Doctor S. Frey (Baden, CH)
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Predicting post operative major adverse cardiovascular events in CABG surgery using ontological relations in machine-learning models to overcome uncertainty
Sir A. Van Der Mee Mendes (Leiden, NL)
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Beyond the risk score

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ESC Digital & AI Summit 2026

13 November 2026 09:30 CET
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Lilly Explore sponsored resources
novartis Explore sponsored resources
novo-nordisk Explore sponsored resources