About AFtoolkit
Open-source AI research from the Artificial Intelligence in Medicine Laboratory
Our Mission
AFtoolkit is an open-source research platform developed to advance the understanding and detection of atrial fibrillation using state-of-the-art deep learning techniques. Our goal is to provide the research community with validated, transparent, and accessible tools for AF analysis and circadian phenotyping.
Team
Artificial Intelligence in Medicine Laboratory (AIM Lab)
Faculty of Biomedical Engineering
Technion - Israel Institute of Technology
The AIM Lab focuses on developing machine learning and deep learning algorithms for cardiovascular signal processing, with particular emphasis on ECG analysis, arrhythmia detection, and personalized medicine approaches.
Key Contributors
Principal Investigators
Prof. Joachim A. Behar
Lead Researcher, AIM Lab
Lead Developers
Shany Biton, Ph.D.
ArNet2 Architecture
Phenotyping Research
Shani Brimer
Circadian Phenotyping
International Collaborators
🇮🇱 Israel
Rambam Health Care Campus
🇯🇵 Japan
Saitama Medical University
🇺🇸 USA
University of Virginia Health System
🇫🇷 France
Université de Lorraine
Research Impact
Publications
Validation Sites
Patients
Featured in:
Nature Portfolio
Machine Learning for Health
Contact
Address
Faculty of Biomedical Engineering
Technion - Israel Institute of Technology
Haifa, Israel
For research inquiries:
aim.lab@technion.ac.il
GitHub
Open source repository:
github.com/aim-lab/AFtoolkit
License & Usage
AFtoolkit is licensed under Creative Commons Attribution-NonCommercial 4.0 (CC BY-NC 4.0)
✓ Allowed
- Research and educational use
- Modification and adaptation
- Redistribution with attribution
- Academic publications
✗ Prohibited
- Commercial use
- Clinical diagnosis
- Patient care decisions
- Medical device integration