A computer-aided approach to the structural analysis and modification of a large circulatory system model

Area of Science:

• Systems Biology
• Computational Physiology
• Medical Informatics

Background:

• Understanding complex physiological systems like the human circulatory system is challenging.
• Large-scale models require sophisticated analysis tools for effective comprehension and modification.
• Existing methods may lack efficient visualization and interactive modification capabilities.

Purpose of the Study:

• To develop an intelligent support system for analyzing and modifying a large human circulatory system model.
• To apply system analysis techniques for visualizing hierarchical relationships within the model.
• To facilitate user interaction for model modification and diagnostic insights.

Main Methods:

• Structural analysis techniques, including model reduction and Interpretative Structural Modeling (ISM).
• Model reduction by removing input-output relations below a specified gain threshold.
• Application of ISM to the reduced model to generate hierarchical directed graphs.

Main Results:

• Visualization of a hierarchy graph illustrating cause-and-effect relationships in the circulatory model.
• Identification of control and diagnostic information through path tracing within the hierarchy.
• Demonstration of the system's capability to allow user modification of the circulatory model.

Conclusions:

• The proposed approach successfully visualizes complex model hierarchies.
• The system provides valuable diagnostic and control information.
• This intelligent system enhances the understanding and modification of large circulatory models.