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Cardiovascular disease risk prediction via machine learning using mental health data

26 August 2022 (08:00 - 19:30)
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Congress Presentation Part of: e-Cardiology/Digital health - Artificial intelligence 2 Artificial Intelligence ESC Professional Premium Access ESC Congress 2022

About the speaker

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Associate Professor Johan Verjans

University of Adelaide, Adelaide (Australia)

6 More presentations in this session

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30 days mortality prediction and risk factor analysis of Asian patients with ACS using interpretable machine learning algorithm
Professor S. Kasim (Kuala Lumpur, MY)
Abstract Slides
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Neuronal nets and logistic regression analysis provide improved prediction of infective endocarditis compared to the modified Duke Score: a post-hoc analysis of the prospective PRO-ENDOCARDITIS study
Doctor L. Vogel (Essen, DE)
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Using artificial intelligence for device identification and characterization in angiographic sequences of TAVI procedures as radiomic biomarkers for prosthesis deterioration
Doctor C. Veiga (Vigo, ES)
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Predicting cardiovascular risk factors from facial & full body photography using deep learning
Mr M. Knorr (Hamburg, DE)
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Detection of left ventricular hypertrophy on the ECG through machine learning with a focus on obesity.
Doctor M. Marketou (Heraklion, GR) Doctor E. Angelaki (Boston, US)
Abstract Slides

Access the full session

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e-Cardiology/Digital health - Artificial intelligence 2

The Event

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ESC Congress 2022

26 August - 29 August 2022
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ESC 365 is supported by

novartis Explore sponsored resources