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Comorbidity neural network model for personalised recommendations in cardiometabolic risk factor management: towards early precision medicine in routine clinical practice

30 August 2024 (08:00 - 17:30)
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Congress Presentation Part of: Machine learning in preventive cardiology Drug therapy ESC Professional Premium Access ESC Congress 2024 European Society of Cardiology

About the speaker

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Mr Yaron Dibner

(Switzerland)

8 More presentations in this session

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Machine learning identifies individuals at higher risk of incident cardio-renal-metabolic diseases and cardiovascular death who have unrealised opportunities to reduce future cardiovascular risk
Doctor M. Haris (Leeds, GB)
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The relationship between retinal vascular parameters measured by artificial intelligence and the risk of new-onset cardiovascular disease in a Chinese community-based population
Doctor F. Fan (Beijing, CN)
Abstract Slides Video
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Predicting atrial fibrillation within 7 years follow-up using machine learning models
Miss K. Tsarapatsani (Ioannina, GR)
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The association between cardiovascular health and physiologic age as determined by artificial intelligence-enabled electrocardiography
Doctor L. Ortega Aviles (Rochester, US)
Abstract Slides Video
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Coronary artery calcium scans powered by artificial intelligence (AI-CAC) predicts atrial fibrillation and stroke comparably to cardiac magnetic resonance imaging: MESA
Doctor M. Naghavi (Houston, US)
Abstract Slides Video

Access the full session

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Machine learning in preventive cardiology

The Event

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ESC Congress 2024

30 August - 2 September 2024
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ESC 365 is supported by

novartis Explore sponsored resources