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The dual model approach represents a promising method for achieving semantic interoperability [ 6].
The dual model approach represents a promising solution for achieving semantically interoperable standardized electronic health record (EHR) exchange.
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As mentioned earlier, when used to handle flux distributions estimated by FBA in genome-scale models, this approach represents an alternative hybrid framework to linear optimization techniques during metabolic target selection, which could significantly surpass existing limitations in modeling complex phenotypes.
WHAT THIS STUDY ADDS TO OUR KNOWLEDGE ☑ This model-based approach represents a tool for integration of knowledge related to disease progression, clinical outcome, dose-limiting toxicities, quality of life, and cost effectiveness, in order to evaluate different potential treatment strategies at early stages of drug development.
Thus, a model developed using this approach represents not only knowledge gained from the current analysis dataset but also potentially all prior knowledge.
The third stage of the mixed effect model approach would represent a Bayesian representation in which the model would contain the prior distributions of the population parameters as mentioned previously.
Apple's approach represents the new marketing model, a shift from monologue to dialogue.
Very recently, Campbell et al. 3 proposed a Markov model approach to represent the states of regulatory units, but the computational costs again limited the number of units studied in the model.
Model-based approaches represent texture using mathematical models such as fractal and stochastic models, and interpret texture by using images generated by models[ 17 20].
The coupling between dynamics and chemistry plays a major role in determining street canyon air quality, and numerical model approaches to represent this coupling are reviewed in this article.
Model-based approaches represent texture using sophisticated mathematical models such as fractal analysis.
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