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

Back

ESC Professional Premium Access

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

Session: Harnessing the power of artificial intelligence in the clinic

Topic: Artificial Intelligence (Machine Learning, Deep Learning)

Speaker: Doctor C. Hayward (Leeds, GB)

Event: ESC Congress 2023

Congress Presentation

Add to my library

About the speaker

Doctor Christopher Hayward

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

0 follower

6 more presentations in this session

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 (Cambridge, US)

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)

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

Speaker: Doctor L. Vogel (Essen, DE)

Access the full session

Harnessing the power of artificial intelligence in the clinic

Speakers: Doctor C. Hayward, Doctor S. Awasthi, Miss N. Kaur, Doctor E. Angelaki, Doctor G. Kowlgi...

Access

About the event

ESC Congress 2023

25 August - 28 August 2023

Sessions Presentations

Congress

ESC 365 is supported by

Explore sponsored resources