High-performance toolkit for aligning and fusing cardiac imaging from CCTA, IVUS, OCT, and MRI.
AI in Cardiovascular Medicine (AI-CVM) at Inselspital, University of Bern, Switzerland
The AI in Cardiovascular Medicine Laboratory (AI-CVM) advances artificial intelligence research in cardiovascular health by developing machine and deep learning techniques to address key challenges in cardiovascular disease. The lab analyzes multimodal data, including clinical text, physiological signals, medical images, videos, electronic health records, and omics data, to derive comprehensive insights into patient health. AI-CVM integrates and develops diverse AI paradigms, including vision foundation models, large language models, vision-language models, and agentic AI, to create intelligent and interpretable systems for cardiovascular medicine. Committed to open science, the lab promotes transparency and collaboration by open-sourcing code, models, and datasets.
Developing open-source clinical decision support systems and AI models for research and practice
Real-world testing and implementation protocols facilitating AI deployment in cardiology practice
Training programs and documentation that bridge AI research and cardiovascular practice
Partnerships across institutions advancing cardiovascular AI together
High-quality, annotated datasets enabling reproducible cardiovascular AI research
High-performance toolkit for aligning and fusing cardiac imaging from CCTA, IVUS, OCT, and MRI.
TAVI-ALPURA is an AI-based tool for predicting long-term mortality after transcatheter aortic valve implantation (TAVI).
AI-powered software for cardiac IVUS analysis with automated segmentation and gating capabilities.
High-performance toolkit for aligning and fusing cardiac imaging from CCTA, IVUS, OCT, and MRI.
Open-source benchmarking framework comparing deep learning architectures for medical segmentation
Isaac Shiri leads AI-CVM lab and group, integrating clinical data, medical images, and health records through multimodal AI. Develops open-source tools and datasets to advance healthcare innovation.
Christoph Gräni is a Professor & Director of Cardiac Imaging at University Hospital Bern. He is an expert in non-invasive cardiovascular imaging (CT, MRI, Nuclear, echocardiography), bridging advanced imaging with clinical AI applications.
Georgios is a Senior Physician in Invasive Cardiology with expertise and interest in data science and AI applications in medicine.
Georgios Siontis, MD, PhD
Moritz is a deputy senior physician in cardiac imaging with a strong interest in AI for outcome prediction in cardiovascular diseases.
Moritz Hundertmark, MD, PhD
Christoph is a physician specializing in cardiac imaging with a strong interest in AI for enhancing clinical workflows.
Christoph Ryffel, MD, PhD
Develops AI-based survival models for cardiovascular risk prediction, integrating multiple data sources to enable personalized patient care.
Giovanni Baj, PhD
Develops digital and physical heart twin models using advanced simulations to enhance the diagnosis and treatment planning of coronary artery disease.
Ali Mokhtari, PhD
Develops AI vision-language models for medical imaging. Active contributor to open-source healthcare AI projects.
Pooya MohammadiKazaj, MSc
Combines medical background with software development expertise to create open-source tools for cardiac image analysis.
Anselm Stark, MD
Develops AI tools for analyzing aortic diseases, combining clinical expertise with computational methods for better diagnosis and risk prediction.
Wen Xie, MD
Uses cardiac MRI and AI to improve diagnosis and treatment of heart muscle diseases like hypertrophic and amyloid cardiomyopathy.
Xuan Ma, MD
Nicola is a medical doctor with expertise and interest in cardiac imaging, focusing on developing prognostic image markers for myocarditis.
Nicola Ciocca , MD
Applies physics principles to AI models (PINNS) for reconstructing high-quality 4D heart flow images from MRI scans.
Zahra Bazghandi, BSc
Works on AI-powered cardiac CT imaging that learns from clinician feedback to improve quantitative accuracy.
Leo Fridolin Weber, MD
Develops AI for cardiac MRI analysis and outcome prediction in myocarditis using interactive learning approaches.
Fabian Egli, MD
Developing agentic AI systems that assists clinicians in clinical decisions through collaborative workflows.
Seyed Amir Ahmad Safavi-Naini, MD-MBA, MME
Develops AI software that make machine learning accessible and transparent for healthcare applications.
Hamed Mirzakhani, MSc
Develops AI for cardiac MRI analysis across different imaging sequences using interactive learning to improve accuracy.
Giulin Tanner, MD
Lea leads data management and coordination of international studies and oversees ethics and registry activities within AI-CVM.
Lea Zurbriggen, MSc
The article highlights how our pioneering tool for detecting and classifying anomalous aortic origin of ...More
Dr. Isaac Shiri won the IEEE Bruce Hasegawa Young Investigator Award in Medical Imaging Science, ...More
Anselm has been awarded the Cardiovascular Research Cluster Bern (CVRC) 2025 Prize for Best Flash ...More
Our recent work on AI-based detection and classification of anomalous aortic origin of coronary arteries ...More
Isaac has received the Young Investigator Award in Valvular Heart Disease at the European Society ...More
At AI-CVM, collaboration drives innovation. We welcome inquiries from engineers, clinicians, researchers, industry partners, and anyone passionate about transforming cardiovascular care through artificial intelligence.
We’re interested in:
Contact us at Isaac.shirilord@insel.ch – we look forward to exploring how we can work together to advance cardiovascular medicine.
