A fully automatic machine-learning algorithm reliably quantifies scar on CMR in post-infarct patients and outperforms humans in predicting arrhythmic events in the international derivate cohort

27 August 2021 (00:00 - 00:00)

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About the speaker

Professor Juerg Schwitter

Lausanne University Hospital, Lausanne (Switzerland)

7 More presentations in this session

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Drug gene interaction in association with novel transcriptomic based plaque phenotypes: a study in symptomatic and asymptomatic human plaques

Professor G. Pasterkamp (Utrecht, NL)

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Activation of the Apelin Receptor by LIT01-196 as a New Strategy for Prevention of Heart Failure After Myocardial Infarction

Doctor P. Girault-Sotias (Montreal, CA)

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Arrhythmogenic Cardiomyopathy is caused by disruption of the desmosomal adhesive interface

Assistant Professor C. Schinner (Bern, CH)

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Prediction of plaque vulnerability and clinical outcome by a deep learning-based algorithm for optical coherence tomography imaging in coronary artery disease

Professor S. Uemura (Kurashiki, JP)

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Convoluted Neural Network ECG classification using Fourier domain shows improved accuracy versus real domain ECG in Atrial Fibrillation using PTB-XL Dataset

Doctor M. Kent (Ann Arbor, US)

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The Event

ESC Congress 2021 - The Digital Experience

27 August - 30 August 2021

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