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The purpose of this study is to show an approach to making an intelligent support system for understanding and modifying a large circulatory system model using techniques of system analysis. Structural analysis makes it possible to visualize hierarchies of Coleman's (1981) circulatory model Human. Two techniques are successively applied for structural analysis, model reduction and graph analysis by interpretative structural modeling (ISM). First, the analysis for model reduction removes input-output relations with an input-output gain less than a given threshold, and second, the ISM technique applied to the reduced model of Human provides hierarchical directed graphs. The proposed approach: (1) enables visualization of a hierarchy graph of cause and effect relations of the large circulatory model, (2) suggests control and diagnostic information to the model by tracing back a path in the hierarchy, and (3) allows the user to modify the circulatory model. The efficiency and performance of the proposed approach demonstrates technical indications of success in analyzing and justifying experimental evidences with the online help of the system.