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Disease trajectories following myocardial infarction: insights from process mining of 145 million hospitalisation episodes

25 August 2023 (07:30 - 18:30)
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Congress Presentation Part of: Harnessing the power of artificial intelligence in the clinic Artificial Intelligence ESC Professional Premium Access ESC Congress 2023 European Society of Cardiology

About the speaker

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Doctor Christopher James Hayward

University of Leeds, Leeds (United Kingdom of Great Britain & Northern Ireland)

6 More presentations in this session

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Risk stratification of coronary artery disease using the artificial intelligence-enabled electrocardiogram
Doctor S. Awasthi (Cambridge, US)
Abstract Slides Video
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Use of machine learning to predict mortality in patients with type 2 diabetes mellitus, according to socioeconomic status
Miss N. Kaur (Glasgow, GB)
Abstract Slides Video
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Single-lead ECG based detection of arterial hypertension using artificial intelligence algorithms
Doctor E. Angelaki (Boston, US)
Abstract Slides Video
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Detection of left ventricular contractile dysfunction in patients with premature ventricular contractions using electrocardiogram trained using a deep learning model
Doctor G. Kowlgi (Rochester, US)
Abstract Slides Video
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Artificial intelligence (AI) enhanced ECG predicts obstructive cardiovascular disease and death using secondary data; a benchmarked comparison of different methods
Doctor L. Vogel (Essen, DE)
Abstract Slides Video

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Harnessing the power of artificial intelligence in the clinic

The Event

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ESC Congress 2023

25 August - 28 August 2023
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ESC 365 is supported by

novartis Explore sponsored resources