Cardiac Digital Twins and AI: From Multi-Modal Modeling to Medical Implementation
A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biosignal Processing".
Deadline for manuscript submissions: 31 January 2026 | Viewed by 43
Special Issue Editors
Interests: AI for healthcare; cardiac digital twins; medical imaging; multimodal AI
Special Issues, Collections and Topics in MDPI journals
Interests: computational modeling; biomedical engineering; numerical methods; mathematical biology; high-performance computing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Cardiac digital twins (CDTs) have the potential to realize the vision of precision cardiology by enabling data-driven patient-specific simulations of cardiac function to inform clinical decision-making. Recent advancements in artificial intelligence (AI) and multi-modal modeling have accelerated the translation of CDTs from theoretical frameworks to clinically actionable solutions, offering unprecedented potential for personalized cardiovascular care.
This Special Issue focuses on the synergy between AI and multi-modal modeling to advance CDTs from research to clinical practice. We welcome original research and comprehensive reviews addressing key themes, such as the following:
- AI-driven strategies for fusing heterogeneous data (e.g., medical imaging, genomics, electrophysiology, and wearable sensors);
- Mechanistic simulations of cardiac pathophysiology and real-time personalized modeling;
- Scalable AI architectures for data integration and uncertainty quantification in model validation;
- Translational approaches for clinical deployment of digital twins (e.g., arrhythmia prediction, drug testing, surgical planning, and closed-loop device control);
- Innovations in model personalization, validation against clinical outcomes, and ethical/regulatory considerations.
By bridging computational bioengineering and clinical cardiology, this issue aims to accelerate the adoption of CDTs as next-generation tools to improve cardiovascular care. We look forward to hearing from you.
Dr. Lei Li
Prof. Dr. Rodrigo Weber Dos Santos
Dr. Julia Camps
Guest Editors
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Keywords
- cardiac digital twins
- multi-modal modeling
- AI in cardiology
- clinical translation
- multi-modal data integration
- personalized cardiac modeling
- real-time simulation
- cardiovascular precision medicine
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