Back
Speaker illustration

Doctor Isaac Shiri

Bern University Hospital, Inselspital, Bern (Switzerland)

Member of:

European Society of Cardiology

As a group leader of artificial intelligence in cardiovascular imaging and head of artificial intelligence in the cardiovascular imaging (AI-CVI) laboratory, Dr. I Shiri, PhD, has expertise in AI for the clinical diagnosis and prognosis of cardiovascular disease. The AI-CVI laboratory has developed various tools for analyzing different modalities to create diagnostic and prognostic tools. These tools consist of analyzing single and multi-modalities, including ECG, clinical data, and various tomography imaging techniques such as CT, MRI, PET, SPECT, and ultrasound. These tools enable automatic quantification, detection, and outcome prediction in cardiovascular imaging.

Presentations

Fully automated 3D body composition analysis in computed tomography: a prognostic imaging biomarker for outcomes after transcatheter aortic valve implantation

Event: ESC Congress 2025

Topic: Valvular Heart Disease

Session: Cardiac computed tomography innovations transforming cardiac care

Access
Like
Thumbnail

Discussion and Q&A

Event: ESC Congress 2025

Topic: Artificial Intelligence

Session: Next-generation cardiac care: the role of artificial intelligence in ATTR cardiomyopathy

Access
Like
Thumbnail

Harnessing artificial intelligence in ATTR cardiomyopathy: current and future perspectives

Event: ESC Congress 2025

Topic: Artificial Intelligence

Session: Next-generation cardiac care: the role of artificial intelligence in ATTR cardiomyopathy

Access
Like
Thumbnail

Fully automated detection of anomalous aortic origin of the coronary arteries in coronary CT images: a novel artificial intelligence-based screening tool

Event: ESC Congress 2024

Topic: Artificial Intelligence

Session: Progress and challenges in artificial intelligence for cardiovascular risk assessment and diagnosis

Access
Like
Thumbnail

Interpretable artificial intelligence-based transthyretin amyloid cardiomyopathy detection in patients with severe aortic stenosis

Event: ESC Congress 2024

Topic: Artificial Intelligence

Session: Artificial intelligence-powered cardiovascular risk assessment: machine learning for disease detection

Access
Like
Thumbnail

Multi-modal artificial intelligence-based prediction for cardiovascular mortality after transcatheter aortic valve implantation: a time-to-event survival prediction

Event: ESC Congress 2024

Topic: Aortic Valve Stenosis

Session: Young Investigator Award Session in Valvular Heart Disease

Access
Like
Thumbnail

ESC 365 is supported by

bristol-myers-squibb Explore sponsored resources
novartis Explore sponsored resources
novo-nordisk Explore sponsored resources