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Time-series clustering of raw recordings of 24-hour ambulatory blood presssure for risk stratification in general population

30 August 2024 (08:00 - 17:30)
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Congress Presentation Part of: Artificial intelligence-powered cardiovascular risk assessment: machine learning for disease detection Artificial Intelligence ESC Professional Premium Access ESC Congress 2024 European Society of Cardiology

About the speaker

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Mr Evangelos Ntalianis

Leuven (Belgium)

8 More presentations in this session

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Identifying at-risk patients for atrial high-rate episodes by machine learning
Doctor Y. Chen (Liverpool, GB)
Abstract Slides Video
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Improving cardiovascular risk stratification with ECG-predicted risk factors in primary prevention
Mr M. Knorr (Hamburg, DE)
Abstract Slides Video
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Improving prognostic accuracy in ischemic cardiomyopathy: the CMR-LGE score
Doctor A. Unger (Brussels, BE)
Abstract Slides Video
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To compare 24 hour blood pressure values of a conventional 24 hours ambulatory blood pressure device versus a wristband using an artificial intelligence algorithm based on photophletysmography
Doctor E. Ronner (Delft, NL)
Abstract Slides Video
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AI-based cluster analysis enables outcomes prediction among patients with increased LVM
Doctor Y. Bitton (Jerusalem, IL)
Abstract Slides Video

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Artificial intelligence-powered cardiovascular risk assessment: machine learning for disease detection

The Event

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ESC Congress 2024

30 August - 2 September 2024
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