Prediction of all-cause mortality in cardiovascular patients by using machine learning models

Back

ESC Professional Premium Access

Prediction of all-cause mortality in cardiovascular patients by using machine learning models

Session: Novel analysis technics in coronary artery disease

Topic: Diagnostic Methods

Speaker: Assistant Professor A. Sakellarios (Heraklion, GR)

Event: ESC Congress 2022

Congress Presentation

Add to my library

About the speaker

Assistant Professor Antonis Sakellarios

Foundation for Research and Technology - Hellas, Heraklion (Greece)

0 follower

5 more presentations in this session

Predicting risk of future acute coronary syndromes, 1-year survival and the need for coronary angiography in unstable angina: A Nationwide Machine Learning Study

Speaker: Doctor A. Myredal (Gothenburg, SE)

Artificial intelligence-guided, single-lead EKG may be a game-changer for symptom-to-balloon time reduction in ST-elevated myocardial infarction

Speaker: Doctor S. Mehta (Miami, US)

Optical Coherence Tomography and Artificial Intelligence for calcium quantification in coronary disease of diabetic patients.

Speaker: Doctor F. Di Muro (Florence, IT)

Deep learning to detect significant coronary artery disease from plain chest radiographs

Speaker: Doctor G. d'ancona (Berlin, DE)

Development and validation of non-invasive endothelial shear stress (ESS) estimations of coronary artery haemodynamics using computational modelling.

Speaker: Doctor J. Chan (Adelaide, AU)

Access the full session

Novel analysis technics in coronary artery disease

Speakers: Assistant Professor A. Sakellarios, Doctor A. Myredal, Doctor S. Mehta, Doctor F. Di Muro, Doctor G. d'ancona...

Access

About the event

ESC Congress 2022

26 August - 29 August 2022

Sessions Presentations

Congress

ESC 365 is supported by

Explore sponsored resources