Hybrid Artificial Intelligence Outcome Prediction Using Feature Extraction from Stress Perfusion Cardiac Magnetic Resonance Images and Electronic Health Records

Back

ESC Professional Premium Access

Hybrid Artificial Intelligence Outcome Prediction Using Feature Extraction from Stress Perfusion Cardiac Magnetic Resonance Images and Electronic Health Records

Session: Artificial intelligence: the new clinical workhorse?

Topic: Artificial Intelligence (Machine Learning, Deep Learning)

Speaker: Doctor E. Alskaf (London, GB)

Event: ESC Congress 2023

Congress Presentation

Add to my library

About the speaker

Doctor Ebraham Alskaf

King's College London, London (United Kingdom of Great Britain & Northern Ireland)

0 follower

6 more presentations in this session

Validation of an artificial intelligence model for 12-lead ECG interpretation

Speaker: Doctor A. Demolder (Aalst, BE)

ChatGPT takes on the european exam in core cardiology: an AI success story

Speaker: Doctor I. Skalidis (Lausanne, CH)

Predicting the risk of in-hospital Asian NSTEMI patients using stacked ensemble learning

Speaker: Professor S. Kasim (Kuala Lumpur, MY)

Performance of modified ResNet model for calcium score from non-contrast computed tomography

Speaker: Doctor E. Tan (Singapore, SG)

Validation of electrocardiographic artificial intelligence model for outcome prediction in patients with heart failure

Speaker: Doctor Y. Cho (Seongnam, KR)

Access the full session

Artificial intelligence: the new clinical workhorse?

Speakers: Doctor E. Alskaf, Doctor A. Demolder, Doctor I. Skalidis, Professor S. Kasim, Doctor E. Tan...

Access

About the event

ESC Congress 2023

25 August - 28 August 2023

Sessions Presentations

Congress

ESC 365 is supported by

Explore sponsored resources