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Bayesian framework allows for uncertainty quantification; hence, it is widely used in integrated prognostics methods.
Probability distributions, on the other hand, allows for uncertainty to be captured in the equation.
This Bayesian-based method allows for uncertainty in fossil calibration points and permits variation in rates of molecular evolution among genes.
Sensitivity analysis allows for uncertainty in the economic evaluation of health care programs.
Bayesian meta-analysis allows for uncertainty in the amount of heterogeneity of treatment effects between studies.
It does not require physicians to explicitly estimate patient risk and it allows for uncertainty in the recommendations.
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Taguchian robust optimization allows for uncertainties in some (environmental) inputs.
The algorithms considered include a Kalman filter that minimizes the estimation error variance, an H∞ filter that minimizes the worst-case estimation error, and a robust mixed Kalman/H∞ filter that allows for uncertainties in both the system and measurement matrices.
The third volume, the planning target volume (PTV), allows for uncertainties in planning or treatment delivery.
The PTV allows for uncertainties in planning or treatment delivery, and is designed to ensure that the radiotherapy dose is actually delivery to the CTV.
Once these two volumes are established, the third volume, the planning target volume (PTV), which allows for uncertainties in planning or delivery, must be added, and the normal tissue structures in the vicinity of the target must be considered.
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