Model validation

Modeling Cardiovascular and Respiratory Dynamics in Congestive Heart Failure

This study develops a coupled cardiovascular-respiratory model that predicts cerebral blood flow velocity (CBFV), arterial blood pressure, end-tidal CO2, and ejection fraction for a patient with congestive heart failure. The model is a lumped parameter model giving rise to a system of ordinary differential equations. We use sensitivity analysis and subset selection to identify a set of model parameters that can be estimated given the patient data. Gradient based nonlinear optimization is used to estimate the subset of parameters.

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