Sentence examples for model for detection of from inspiring English sources

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.

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.

Our aim is to develop a regression model for detection of major genes controlling phenotypic variance that can be applied genome wide.

In conclusion, we have developed a regression model for detection of major loci controlling phenotypic variance, which can be applied on a wide range of experimental crosses such as backcross, F2, and MAGIC lines such as the CC.

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.

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.

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.

However, too many model parameters make the 2D model unsuitable for detection of range-spread targets, particularly, for detection of high-speed manoeuvring ones in strong noise or clutter.

Many studies use color space models (CSM) and color distribution models (CDM) for detection of faces in an image.