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The knowledge of these models is also necessary for dynamic simulation and for the design of control algorithms in order to achieve energy and economic optimizations.
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To our knowledge none of these models have been used specifically for DNT testing up to this date.
To our knowledge none of these models take into account the dynamics between nurse-to-patient ratios, skill mix, nurses' education level, the nursing work environment on one hand and nurse outcomes (nurse retention, job satisfaction, burnout) and patient outcomes on the other hand.
The full knowledge of the model itself is not required.
The MA still required some knowledge of the model in order to set adequate optimization parameters.
First, we validated the filtering method considering perfect knowledge of the model.
We can notice that the performance is very close to an exact knowledge of the model.
First, the method with perfect knowledge of the model was validated in Fig. 8.
In addition, it requires prior knowledge of the system (mainly prior knowledge of the model-describing parameters to be learned).
We tested both PF and PMCMC methods, that is, with and without full knowledge of the model, respectively.
However, knowledge regarding integration of these models in generalist palliative care is yet to be explored.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com