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AI-driven electromechanical model for non-invasive CAD risk assessment across symptom profiles

29 August 2026 (10:15 - 11:00)
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Congress Presentation Part of: Artificial intelligence and multimodal imaging for prediction, diagnosis, and prognostication of coronary artery disease Noninvasive Diagnostic Methods ESC2026 Premium Access ESC Congress 2026 European Society of Cardiology

About the speaker

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Professor Richard Kobza

Cardiopuls Medical Centre, Luzern (Switzerland)

6 More presentations in this session

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Diagnostic and prognostic value of growth differentiation factor 15 in suspected functionally relevant coronary artery disease
Ms F. Nafaa (Basel, CH)
Abstract Slides Video
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Incremental value of coronary computed tomography angiography-derived wall shear stress over stenosis grade in detecting significant coronary artery disease
Mr K. Sadowski (Warsaw, PL)
Abstract Slides Video
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AI-based coronary artery disease stratification integrating clinical, lipidomic, and transcriptomic data
Assistant Professor A. Sakellarios (Rio-Patras, GR)
Abstract Slides Video
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A CMR‑based multimodal model to guide invasive angiography referral in patients with suspected obstructive coronary artery disease
Professor F. Cao (Beijing, CN)
Abstract Slides Video
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Incremental value of abdominal adipose tissue distribution and CT-derived radiomics over clinical risk factors for coronary artery disease prediction: a nested model comparison
Miss F. Nunes (Vila Nova de Gaia, PT)
Abstract Slides Video

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Artificial intelligence and multimodal imaging for prediction, diagnosis, and prognostication of coronary artery disease

The Event

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ESC Congress 2026

29 August 2026 10:15 CET
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