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Predicting anaerobic threshold from warmup exercise by machine learning technique for daily appropriate exercise in patients with cardiovascular diseases

31 August 2026 (11:15 - 12:00)
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Congress Presentation Part of: Artificial intelligence modelling and cardiovascular disease Exercise Testing ESC2026 Premium Access ESC Congress 2026 European Society of Cardiology

About the speaker

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Associate Professor Yasunori Suematsu

Fukuoka University School of Medicine, Fukuoka (Japan)

5 More presentations in this session

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Machine learning approach to identify clusters of patients with distinct cardiac chronotropic response during incremental exercise
Mr A. Rammal (Paris, FR)
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Ultra-short-term triggering of acute heart failure by heat following the monsoon rainy season: an hourly resolution case-crossover study in older adults
Doctor R. Fujimoto (Tsuyama, JP)
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Explainable machine learning for the identification of proteins associated with cardiorespiratory fitness
Mr E. Santana (Leuven, BE)
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Age and sex modify the relationship between long-term depressive symptoms and heart rate variability
Ms N. Ntlapo (Rotterdam, NL)
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Sex-differential susceptibility to particulate air pollution and ischaemic heart disease: integrating human metabolomics with global burden modelling
Doctor S. Fathieh (London, GB)
Abstract

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Artificial intelligence modelling and cardiovascular disease

The Event

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ESC Congress 2026

31 August 2026 11:15 CET
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