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Possible monitoring systems are based on a combination of different technical solutions for each of the MCYFS components, and are evaluated through an automatic algorithm that calculates the expected system performance –relying on a priori expert judgement–, the costs, and possible risks to construct some technical solutions, to finally identify the cost-efficient ones.
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Once validated, mtDNA content could be incorporated with other available risk factors to construct a multivariate risk assessment model for identifying subjects with high risk of glioma.
Similarly, we combined subjects with five or six risk alleles to construct the highest-risk group.
We used competing risk methodology to construct this conceptualized model because patients who survive longer remain at risk for an appropriate ICD shock, whereas those who die are no longer at risk for an arrhythmic event.
This will be instrumental to preventing over-reliance on one or other economic activity and thereby will assist pastoralists to manage risk and to construct more resilient livelihoods.
To reduce the redundancy and identify interaction partners of special interest we used the information from all significant network modules within risk groups to construct consensus networks.
To further assess the diagnostic usefulness of the selected four serum miRNAs in discriminating between AD and controls, we conducted a risk score analysis to construct a signature using these 4 miRNAs.
The results of the simulations were used to calculate the incremental benefits and risks for all anticoagulants which were subsequently used to construct risk-benefit planes.
Furthermore, our goal was not to understand other factors impacting the risk of SHEs, but to construct a set of parameters relating the risk to treatment groups used in clinical practice.
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