Neural network-derived electrocardiographic features have prognostic significance and important phenotypic and genotypic associations

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Neural network-derived electrocardiographic features have prognostic significance and important phenotypic and genotypic associations

Session: The latest in cardiovascular diagnostics supported by artificial intelligence

Topic: Artificial Intelligence (Machine Learning, Deep Learning)

Speaker: Doctor L. Pastika (London, GB)

Event: ESC Congress 2023

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Doctor Libor Pastika

Imperial College London, London (United Kingdom of Great Britain & Northern Ireland)

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State-of-the-art lecture on artificial intelligence in cardiology

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Artificial intelligence-derived ECG bio-index as a tool for predicting the prognosis of patients with ST-segment elevation myocardial infarction underwent primary percutaneous coronary intervention

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Reducing the burden of inconclusive smart-device single-lead ECG tracings via a novel atificial intelligence algorithm

Speaker: Mr S. Weidlich (Basel, CH)

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The latest in cardiovascular diagnostics supported by artificial intelligence

Speakers: Doctor L. Pastika, Professor U. Landmesser, Assistant Professor K. Jeon, Doctor E. Ronner, Mr S. Weidlich

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ESC Congress 2023

25 August - 28 August 2023

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