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For this purpose, the use of Value of Information (VOI) methods can conceptually and quantitatively offer a sound way to identify evidence gaps and prioritise future research [ 18, 19], thereby supporting the decision-making as to whether additional research is justified.
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Although validated in the context of 2009 H1N1 influenza virus, the same method can conceptually be extended to other seasonal and pandemic influenzas, simply by expression of the corresponding specific recombinant protein HA50 274.
Given the nature of this analysis, these methods can be conceptually challenging and rely highly on a number of assumptions [28, 29].
Several conceptually simple methods can also be employed to effectively combine uncertainty with spatial estimates, including color saturation, where highest uncertainty is depicted by desaturated colors (de Cola 2002), or decreasing boundary crispness with increased uncertainty.
While conceptually appealing, these methods can be difficult to implement thereby limiting their utility.
Much better a place where you can conceptually put your feet up.
Methods can be copied.
The three layers can conceptually be regarded as three phases of the integration process.
Moreover, our method can be readily generalized beyond the domain of perception, for example, to estimate conceptually abstract priors such as over moral beliefs by modeling subjects' responses to questionnaires using ideal observer models derived from item response theory [ 39].
The proposed bootstrap method is conceptually straightforward, but can be computationally expensive at the genome-wide level.
However, the two methods are conceptually different.
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