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Interpretable artificial intelligence-based transthyretin amyloid cardiomyopathy detection in patients with severe aortic stenosis

1 September 2024 (14:00 - 14:50)
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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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Doctor Isaac Shiri

Bern University Hospital, Inselspital, Bern (Switzerland)

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)
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Improving cardiovascular risk stratification with ECG-predicted risk factors in primary prevention
Mr M. Knorr (Hamburg, DE)
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Improving prognostic accuracy in ischemic cardiomyopathy: the CMR-LGE score
Doctor A. Unger (Brussels, BE)
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Time-series clustering of raw recordings of 24-hour ambulatory blood presssure for risk stratification in general population
Mr E. Ntalianis (Leuven, BE)
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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)
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Artificial intelligence-powered cardiovascular risk assessment: machine learning for disease detection

The Event

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ESC Congress 2024

1 September 2024 14:00 CET
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novartis Explore sponsored resources