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Using artificial intelligence for device identification and characterization in angiographic sequences of TAVI procedures as radiomic biomarkers for prosthesis deterioration

Topic: Artificial Intelligence (Machine Learning, Deep Learning)

Congress Session

About the speaker

Doctor Cesar Veiga

University Hospital Alvaro Cunqueiro, Vigo (Spain)
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6 more presentations in this session

30 days mortality prediction and risk factor analysis of Asian patients with ACS using interpretable machine learning algorithm

Speaker: Professor S. Kasim (Kuala Lumpur, MY)

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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

Speaker: Doctor L. Vogel (Essen, DE)

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Predicting cardiovascular risk factors from facial & full body photography using deep learning

Speaker: Mr M. Knorr (Hamburg, DE)

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Cardiovascular disease risk prediction via machine learning using mental health data

Speaker: Doctor J. Verjans (Adelaide, AU)

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Detection of left ventricular hypertrophy on the ECG through machine learning with a focus on obesity.

Speaker: Doctor M. Marketou (Heraklion, GR) Mrs E. Angelaki-Kaxiras (GR)

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Access the full session

e-Cardiology/Digital health - Artificial intelligence 2

Speakers: Doctor C. Veiga, Professor S. Kasim, Doctor L. Vogel, Mr M. Knorr, Doctor J. Verjans...
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About the event

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ESC Congress 2022

26 August - 29 August 2022

Sessions Presentations

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