Back

Diagnosis and prognosis of coronary artery disease using artificial intelligence and nuclear cardiology: A systematic review

31 August 2025 (16:15 - 17:00)
Organised by: Logo
Congress Presentation Part of: Nuclear cardiology innovations Single Photon Emission Computed Tomography (SPECT) ESC Professional Premium Access ESC Congress 2025 European Society of Cardiology

About the speaker

Photo
Doctor Yuchen Dai

University of Toronto, Toronto (Canada)

6 More presentations in this session

Presentation thumbnail
Evaluation of the 2024 European Society of Cardiology risk-factor and calcium score-weighted clinical likelihoods as gatekeeper for patients with suspected chronic coronary syndrome referred for PET
Doctor S. Frey (Basel, CH)
Abstract Slides Video
Presentation thumbnail
Prognostic utility of quantitative positron emission tomography in patients with prior coronary artery bypass grafting: incremental value of myocardial flow reserve and coronary vascular resistance
Doctor Y. Kadoya (Ottawa, CA)
Abstract Slides Video
Presentation thumbnail
The role of Q-SPECT CT in identifying post-pulmonary embolism sequelae
Mrs G. Sorici (Chisinau, MD)
Abstract Slides Video
Presentation thumbnail
Prognostic factors in familial hypercholesterolemia : insights from NH3-PET imaging
Doctor A. Sakai (Tokyo, JP)
Abstract Slides Video
Presentation thumbnail
Complex ventricular arrhythmias are not associated with severity of mitral regurgitation in patients with arrhythmic mitral valve prolapse
Doctor R. Vazirani Ballesteros (Madrid, ES)
Abstract Slides Video

Access the full session

Session thumbnail
Nuclear cardiology innovations

The Event

Event poster

ESC Congress 2025

31 August 2025 16:15 CET
You may be interested in
thumbnail
Congress Presentation
Feasibility of utilizing machine learning to detect coronary artery disease via wearable devices
thumbnail
Congress Session
Foundation models and chatbots in cardiovascular medicine: beyond ChatGPT
thumbnail
Congress Presentation
Lipidomics-based deep learning algorithms can enhance prediction of obstructive coronary artery disease

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources