Structural global parameter identifiability indicates whether one can determine a parameter's value in an ODE model from given inputs and outputs. If a given model has parameters for which there is exactly one value, such parameters are called identifiable. We present a procedure for replacing, if possible, a given ODE model involving not identifiable parameters by an equivalent one such that the new set of parameters is identifiable. We first derive this as an algorithm for one-dimensional ODE models and then reuse this approach for higher-dimensional models.
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