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Single-to-several marker models have at best shown a sensitivity/specificity of 0.87/0.83 in infants [ 16].
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Moreover, a multi-marker model has been assembled which accurately distinguishing patients with NSCLC from smokers with no known malignancies.
Kinematic models are commonly used to quantify foot and ankle kinematics, yet no marker sets or models have been proven reliable or accurate when wearing shoes.
Additionally pig models have identified markers for puerperal psychosis [ 30] and RACK1 as a marker of malignancy for human melanocytic proliferation [ 31].
Our previous studies using single-marker association (i.e. mixed linear models) have identified sites of SNPs in several candidate genes that located in close proximity to the causal polymorphisms or even the functional variant itself for growth and wood-property traits.
Many different models have been proposed to simultaneously estimate marker effects [ 2, 8].
The new models have a curved case with a different, more attractive marker font and come in all of the Aircraft-8 colors.
Several GS models have been developed for predicting phenotypes using large numbers of markers.
The use of surrogate markers or development of identification models has been popular in the identification of cases of healthcare-associated infection since 2000.
Given the important role that has been suggested for chronic inflammation in obese states and its causal role in mediating insulin resistance in peripheral tissues (24), incorporating novel inflammatory markers into diabetes risk prediction models has recently raised interest (25– 25).
All three models had almost identical accuracies except when the number of observations exceeded the number of markers and the marker effects had a non-null mean.
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