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We present a mathematical model that helps define critical components of AD pathogenesis based on differential rate equations that represent the known cross-talks involving microglia, astroglia, neurons, and amyloid-β (Aβ).
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Neither did we have patient-level data to apply some type of quality-adjustment based on differential mortality rates across hospitals as a measure of quality.
To assess if the nodal splits derived based on differential risk of AIDS development also conveyed differential rates of disease progression, we plotted KM plots for each binary split shown in the decision tree (Figure 2C).
As a starting model, we selected a nonlinear model adapted from Samtani based on differential equations with an evolving disease progression rate.
Shebalin et al. (2011) suggested a method based on differential probability gains to convert alarm-based to rate-based earthquake forecast models.
As such, the use of non-exclusion based diagnosis as the core gold standard will produce different prevalence rates than those based on differential diagnosis.
This demonstrates that a combination of forecast models based on differential probability gains can increase earthquake probabilities in rate-based forecast models.
This difference indicates that the combination based on differential probability gain is currently better than a linear combination at increasing the predicted event rates in the limit of high rate values.
The modeling approach is based on differential geometry.
Mathematical models based on differential equations have proved very useful.
Thus, interaction based on differential treatment is unlikely.
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