Computational Cardiology

Aims and Scope

Computational Cardiology publishes research in cardiovascular modeling, electrophysiology, signal analysis, imaging, hemodynamics, digital twins, and AI-driven cardiovascular decision support. The journal emphasizes quantitative and computational approaches that improve understanding, diagnosis, procedural planning, and risk prediction in heart disease.

The field is moving rapidly toward patient-specific digital twins, predictive ECG analytics, virtual surgery planning, precision hemodynamics, and intelligent implantable devices. The journal welcomes both methodological innovation and clinically relevant computational investigations.

Areas of Interest

• Patient-specific digital twins of the heart
• AI-driven electrophysiology and arrhythmia prediction
• Computational ECG and signal analysis
• Virtual procedural planning and ablation mapping
• Stent optimization and cardiovascular flow simulation
• Precision hemodynamics and fluid-structure interaction
• Smart implantable devices and AI-on-a-chip systems
• Leadless pacemaker optimization and adaptive control
• Automated cardiac image segmentation
• Quantitative chamber and wall-motion analysis
• Cardiovascular risk modeling and prediction
• Digital cardiology and real-time computational monitoring

Article Types

• Original Research Articles
• Review Articles
• Mini-reviews
• Methods Papers
• Editorials
• Perspective Articles

Open Access Policy

All articles are published open access under the Creative Commons CC BY 4.0 license.
During the launch phase the article processing charge is $0.