Multimodal machine learning-based technical success prediction in patients undergoing transcatheter aortic valve implantation

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Multimodal machine learning-based technical success prediction in patients undergoing transcatheter aortic valve implantation

Session: Applying digital health to valvular heart disease

Topic: Intervention

Speaker: Doctor D. Tomii (Bern, CH)

Event: ESC Congress 2024

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Doctor Daijiro Tomii

Bern University Hospital, Inselspital, Bern (Switzerland)

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6 more presentations in this session

Prognostic stratification of patients with mitral regurgitation using artificial intelligence-enhanced electrocardiogram for left ventricular diastolic function assessment

Speaker: Doctor G. Tsaban (Rochester, US)

A new wearable cardiac acoustic monitoring technology for the evaluation of subclinical leaflet thrombosis after transcatheter aortic valve replacement: a pilot study

Speaker: Mrs R. Liu (Beijing, CN)

Fully automated CT analysis with a deep-learning based algorithm for pre-procedural planning in transcatheter aortic valve implantation

Speaker: Doctor M. Arsalan (Giessen, DE)

Electrocardiographic criteria for the diagnosis of left ventricular hypertrophy in patients with severe aortic stenosis

Speaker: Doctor V. Emer Egypto Rosa (Sao Paulo, BR)

Magnetocardiographic imaging of Tpeak-Tend magnetic field dynamics discriminates between ventricular repolarization disorders due to mitral valve prolapse and to ischemic heart disease

Speaker: Associate Professor R. Fenici (Rome, IT)

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Applying digital health to valvular heart disease

Speakers: Doctor D. Tomii, Doctor G. Tsaban, Mrs R. Liu, Doctor M. Arsalan, Doctor V. Emer Egypto Rosa...

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ESC Congress 2024

30 August - 2 September 2024

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