Mathematical and Computer Modelling of Dynamical Systems

Computational modelling of physiology has a long successful history as a unique tool to understand the very complex biological function from cellular to tissue and organ levels. The cardiovascular system has been a very active area in which computational methods have played vital roles, from fundamental research to clinical patient management. With the development of computer technology, the fusion of classical PDE based computational methods and advanced techniques such as artificial intelligence (AI) has been at the frontier of computational modelling of the cardiovascular system. The objective of this research topic is to spotlight the latest advances of computational methods in the cardiovascular system, from modelling, and numerical methods to data processing.

The promising role of computational methods in cardiovascular system research has been proven in recent decades. In recent years, numerous sophisticated numerical methods coupled with the patient-specific model have been developed, which benefit the further revelation of the underlying mechanisms and facilitate more precise clinical management of cardiovascular diseases. However, the increasing complexity of the numerical modelling techniques induced difficulties in model preparation and required higher computational costs, which restricted their applications instead. The latest development of high-performance computation as well as AI has shown their ability to solve complex physiological problems, which provided a viable way of overcoming the drawbacks of deploying traditional computational methods in the cardiovascular system. The fusion of such advanced techniques and traditional computational methods has been another cutting-edge area in cardiovascular system research.

We welcome review and original articles describing new mathematical models, in-depth theoretical analysis, reduced-modelling, cutting-edge computational methods, novel statistical approaches, and machine-learning methods for analyzing and modelling the cardiovascular system. We welcome submissions related to but not limited to the following research fields:

• Computational 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 and multiscale modelling and analysis from cell to tissue and the whole heart, such as action potential propagation, calcium dynamics, and electromechanical coupling applied to the diagnosis or treatment of cardiac diseases;
• Personalized modelling development: clinical data assimilation, parameter estimation, uncertainty quantification, etc.;
• High performance computation methods
• AI-accelerated computation methods.

All manuscripts submitted to this Article Collection will undergo a full peer-review; the Guest Advisor for this collection will not be handling the manuscripts (unless they are an Editorial Board member). Please review the journal scope and author submission instructions prior to submitting a manuscript.

The deadline for submitting manuscripts is 30th November 2023.

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Prof. Cai Li is the director of NPU-UoG International Cooperative Lab for Computation & Application in Cardiology, and is the vice director of Xi’an Key Laboratory of Scientific Computation and Applied Statistics. More than 80 papers are published about computational cardiology, theory and its application of numerical methods for PDEs, and biomedical statistics and intelligent medicine.

Dr. Gao primary research interest lies in developing mathematical models for studying biological systems with a focus on clinical image-derived models of the cardiovascular system through close collaboration with clinicians and statisticians. Dr. Gao has been developing image-derived biomechanical models for arteries, heart, mitral valve, cardiac electrophysiology for more than 15 years.

Dr. Guangyu Zhu is an active researcher focus on the hemodynamics in cardiovascular system, artificial heart valve design and machine learning in patient-specific modelling. He is the PI of two grants from National Nature Science Foundation of China.

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