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The mechanisms underlying the development of TdP and the factors that increase the risk of TdP are described and applied to the design of preclinical experimental models for detection of proarrhythmic drug actions.
Using our NotI-microarray data, we attempted to construct prediction models for detection of prostate cancer and discrimination between aggressive and nonaggressive subtypes.
The significance of these changes in the carcinogenic process is discussed, and a possible use of these models for detection of hepatotropic agents and agents causing aneuploidy (clastogens and turbagens) is proposed.
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There is no model for detection.
Moreover, geophysical modeling for detection of deep structures is included in the GEMex project.
Linda et al. [44] presented an IDS using NN-based modeling for detection of anomalous activities.
The watch runs a distinct model for detection that isn't as large as the full neural network running on the iPhone or as small as the initial detector.
Leemput et al. [58] designed an automated method by using an intensity-based tissue classification and a stochastic model for detection of MS lesions from 3-D images.
This method overcomes some limitations of logistic regression modeling for detection and characterization of gene-gene interactions.
The detection efficiency of GFP was estimated by fitting the observed number of bleaching steps to a binomial model for detection.
We performed a cross-sectional analysis of data from a national colonoscopy screening programme to derive and validate a risk prediction model for detection of advanced colorectal neoplasia.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com