Back
EACVI Premium Access

Machine learning outcome prediction using stress perfusion cardiac magnetic resonance and electronic health records

Session: Coronary Artery Disease 3
Topic: Artificial Intelligence (Machine Learning, Deep Learning)
Speaker: Doctor E. Alskaf (London, GB)
Event: EACVI 2023

Congress Presentation

Add to my library

Like

About the speaker

Doctor Ebraham Alskaf

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

5 more presentations in this session

Inflammation and coronary flow reserve in chronic stable coronary artery disease: Evidence for a long standing interplay

Speaker: Doctor I. Armenis (Nicosia, CY)

Access
Abstract
Slides
Like
Thumbnail

Quantification of myocardial blood flow using stress cardiac magnetic resonance for the detection of coronary artery disease

Speaker: Doctor A. Patel (Charlottesville, US)

Access
Abstract
Slides
Like
Thumbnail

Cardiac magnetic resonance in suspected MINOCA patients, clinical and imaging profile, diagnostic performance and 1 year clinical follow up.

Speaker: Doctor A. Rodriguez Perez (Barcelona, ES)

Access
Abstract
Slides
Like
Thumbnail

Troponin and NT-proBNP in the prediction of impaired myocardial deformation after STEMI

Speaker: Miss R. Tomoaia (Leeds, GB)

Access
Abstract
Slides
Like
Thumbnail

Coronary artery calcium identified on non-gated chest CT scans - A wasted opportunity to avoid the tragedy

Speaker: Doctor A. Martins (Lisbon, PT)

Access
Abstract
Slides
Like
Thumbnail

Access the full session

Coronary Artery Disease 3

Speakers: Doctor E. Alskaf, Doctor I. Armenis, Doctor A. Patel, Doctor A. Rodriguez Perez, Miss R. Tomoaia...
Access
Like
Thumbnail

About the event

Image

EACVI 2023

10 May - 12 May 2023

Sessions Presentations

Congress
logo Image

ESC 365 is supported by

logo Bristol Myers Squibb Explore sponsored resources
logo Novo Nordisk Explore sponsored resources