Parameter Inference in the Pulmonary Circulation of Mice
نویسندگان
چکیده
This study focuses on parameter inference in a pulmonary blood circulation model for mice. It utilises a fluid dynamics network model that takes selected parameter values and aims to mimic features of the pulmonary haemodynamics under normal physiological and pathological conditions. This is of medical relevance as it allows monitoring of the progression of pulmonary hypertension. Constraint nonlinear optimization is successfully used to learn the parameter values.
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