Artificial intelligence (AI) enhanced ECG predicts obstructive cardiovascular disease and death using secondary data; a benchmarked comparison of different methods

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Artificial intelligence (AI) enhanced ECG predicts obstructive cardiovascular disease and death using secondary data; a benchmarked comparison of different methods

Session: Harnessing the power of artificial intelligence in the clinic

Topic: Artificial Intelligence (Machine Learning, Deep Learning)

Speaker: Mr L. Vogel (Essen, DE)

Event: ESC Congress 2023

Congress Presentation

About the speaker

Mr Lukas Hermann Vogel

University of Duisburg-Essen - West-German Heart and Vascular Center, Essen (Germany)

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6 more presentations in this session

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

Speaker: Doctor C. Hayward (Leeds, GB)

Risk stratification of coronary artery disease using the artificial intelligence-enabled electrocardiogram

Speaker: Doctor S. Awasthi (Cambridge, US)

Use of machine learning to predict mortality in patients with type 2 diabetes mellitus, according to socioeconomic status

Speaker: Miss N. Kaur (Glasgow, GB)

Single-lead ECG based detection of arterial hypertension using artificial intelligence algorithms

Speaker: Doctor E. Angelaki (Heraklion, GR)

Detection of left ventricular contractile dysfunction in patients with premature ventricular contractions using electrocardiogram trained using a deep learning model

Speaker: Doctor G. Kowlgi (Rochester, US)

Access the full session

Harnessing the power of artificial intelligence in the clinic

Speakers: Mr L. Vogel, Doctor C. Hayward, Doctor S. Awasthi, Miss N. Kaur, Doctor E. Angelaki...

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About the event

ESC Congress 2023

25 August - 28 August 2023

Sessions Presentations

Congress

Artificial intelligence (AI) enhanced ECG predicts obstructive cardiovascular disease and death using secondary data; a benchmarked comparison of different methods

About the speaker

Mr Lukas Hermann Vogel

6 more presentations in this session

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

Risk stratification of coronary artery disease using the artificial intelligence-enabled electrocardiogram

Use of machine learning to predict mortality in patients with type 2 diabetes mellitus, according to socioeconomic status

Single-lead ECG based detection of arterial hypertension using artificial intelligence algorithms

Detection of left ventricular contractile dysfunction in patients with premature ventricular contractions using electrocardiogram trained using a deep learning model

Access the full session

Harnessing the power of artificial intelligence in the clinic

About the event

ESC Congress 2023

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