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Thus, baseline characteristics are more critical than treatment agents for predicting favourable clinical efficacy in RA patients with HDA.
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We evaluated the usefulness of linezolid as a surrogate agent for predicting the susceptibility of clinically significant Gram-positive pathogens to tedizolid.
Due to the inherent heterogeneity and distribution in data that used to predict RSA and high time costs of central data mining on large training data, the necessity of an agent-based architecture for predicting RSA, seems to be essential.
On the other hand, empirical models of tumor growth kinetics have been employed for decades as tools to interpret dose response relationships and compare agents, and more recently for predicting outcomes of clinical trials based on preliminary tumor size measurements.
Therefore, these vasoactive agents may be promising biomarkers for predicting preeclampsia in early gestation.
Not surprisingly, treatment with a CT drug as opposed to a non-CT agent was an independent variable for predicting grade 3 or 4 toxicity.
Many believe that the lack of a validated biomarker for predicting benefit to antiangiogenic agents has severely limited the optimal clinical development of these agents.
An original agent-based model (ABM) was designed for predicting the prevalence (i.e., proportion of infected individuals in the total population at a given time) of T. cruzi I and II during single and mixed infections.
I expect this will happen: like humans, AI agents will need to have a basis for predicting what other machines will do.
Others have reviewed multi-gene signatures for predicting sensitivity to specific agents [ 44, 45].
It provides tools for predicting what will happen when agents with conflicting interests interact [20].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com