Sentence examples for most appropriate predictive from inspiring English sources

The proposed criterion helps to cluster the seismic intensity parameters, which exhibit the most appropriate predictive equations.

As a result, numerical modeling seems to be the most appropriate predictive approach and, in particular, the Discrete Element Method (DEM) has recently emerged as a very promising tool for this purpose.

A sodium level less than or equal to 125 mmol/l had the highest accuracy, therefore, it was the most appropriate predictive parameter.

The algorithm with the most appropriate predictive capabilities contains two demographic variables (gender and age), one clinical (BMI) and 3 items of the preoperative WOMAC questionnaire (two pain-related and one function scale).

The lowest values of DIC will point to the most appropriate models in predictive terms.

Consequently, we focused only on the skeletal muscle as the most appropriate tissue for deriving the predictive models of interest.

While proved to be useful for association testing, however, it has been argued that the statistics being used to identify variants or their combinations, typically p-values for disease risk association, are perhaps not the most appropriate means for evaluating the predictive or clinical value of the genetic profiles [ 33].

This study suggests that foot length is the most appropriate predictor for LBW given its high predictive values and ease of measurement in comparison to head, chest, thigh and mid-upper arm circumference.

Such a personalized therapy, based on the predictive markers, may provide the most appropriate and efficient treatment for a specific subset of patients.

As it was mentioned previously, when a physical chemistry expert develops a QSAR/QSPR predictive model, the choice of the most appropriate descriptors for this model constitutes the first complex challenge.

This method was applied to a number of model designs to assess the tradeoff between model complexity, accuracy and predictive uncertainty, and to identify the most appropriate model design under specific climatic conditions.