Sentence examples for value in classifying from inspiring English sources

Oral and pharyngeal teeth are of great value in classifying many families of ostariophysans.

Although specific SNPs in genes that metabolize triptans have yet to be identified, current pharmacogenetics studies indicate that defining the effect SNPs have on drug metabolism and treatment response may have value in classifying patients into groups of poor metabolizers to predict therapeutic responses and to evaluate sex differences.

As each information source is brought into the KB, we will empirically assess its added value in classifying drug outcome pairs.

Apart from Mendelian forms of obesity, the use of genetic information alone will provide only limited predictive value in classifying young people at high risk for the development of childhood obesity.

These results suggest that further analyses into those with multiple admissions would indeed be of value in classifying the frailest among this population as it is a common problem among older people and drive a large part of the burden and costs associated with frailty.

Echocardiography has value in classifying patients with myocarditis and may provide prognostic information.

In conclusion, our results demonstrate the degree of inaccuracy of parent-reported weight and height values in classifying preschool children as being underweight, overweight or obese.

The area under the curve (AUC) of receiver operating characteristic plots, obtained by NEMO score sensitivity and specificity values in classifying patients with ESSG index ≥3.5, was significantly higher than the corresponding AUC derived from either GC or Cs scores (P <0.03 and P <0.0006, respectively).

The importance of acoustic features in estimating the emotion primitive values and in classifying emotions into categories was also investigated.

The upper and lower threshold values would assist in classifying various dependencies from user requirements.

ROC analyses supported the value of these measures in classifying responders/non-responders. Our results suggest that fronto-temporal connectivity strengths could be potential biomarkers to differentiate responders and slow responders or non-responders in MDD.