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Doctor Isaac Shiri

Bern University Hospital, Inselspital, Bern (Switzerland)

Member of:

European Society of Cardiology

As head of the Artificial Intelligence in Cardiovascular Medicine (AI-CVM) group and laboratory, Dr. I. Shiri, PhD, specializes in applying artificial intelligence to the clinical diagnosis and prognosis of cardiovascular disease. The AI-CVM Laboratory primarily focuses on cutting-edge research in machine learning (ML) and deep learning (DL) applications within cardiovascular medicine. The laboratory’s mission is to address a broad range of health-related questions through multimodal information analysis, leveraging diverse datasets that include text, signals, and medical images from various modalities.

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

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Discussion and Q&A

Event: ESC Congress 2025

Topic: Artificial Intelligence

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

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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

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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

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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

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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

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