Manuscript Topics
Mathematical modelling of physiology has enjoyed a long successful history as a unique tool to understand the very complex biological function from the cellular levels to the tissue levels and the organ levels.  Recent advancements in mathematical modelling in physiology have ranged from understanding the basic biological system, such as cellular behaviours, to predictive personalized computational models which can improve current patient management in the clinic. The cardiovascular system is a very active area where mathematical modelling has made tremendous advances, and are being silently revolutionizing the clinical practice, towards precision medicine in cardiology. There is an urgent need to promote multidisciplinary collaborations from mathematics, computational modelling, bioengineering, experiments and clinic science. The objective of this research topic is to place the spotlight on the mathematical modelling of the cardiovascular system by integrating mathematical analysis and modelling with the complex biological system and to promote and foster the development of mathematical modelling in physiology, in particular cardiology.

This research topic will focus on mathematical modelling of the cardiovascular system including both the heart and the blood vessels, which has been at the frontier of mathematical modelling both for understanding physiology and pathology. We welcome review and original articles describing new mathematical models, in-depth theoretical analysis, reduced-modelling, cutting-edge computational methods, novel statistical approach and machine-learning methods for analysing and modelling physiological processes. We welcome submissions related to but not limited to the following research fields:

• Multi-scale and multi-physics biomechanical modelling and analysis of the cardiac system from the cell, the tissue structure to the whole heart function, i.e., myocardium, valves and arterial wall, etc.;
• Hemodynamic modelling  and analysis in large and small vessels, including systemic circulation, coronary circulation, atherosclerosis, etc;
• Electrophysiology modelling and analysis from cell to tissue and the whole heart, such as action potential propagation, calcium dynamics, electromechanical coupling applied to diagnosis or treatment of cardiac diseases;
• Personalized modelling development: clinical data assimilation, parameter estimation, uncertainty quantification, etc.;
• Machine learning methods for reduced modelling.

We also welcome any other research articles in mathematical modelling of physiology that are relevant to various clinical diseases, like bone, brain and others.

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