Sentence examples for decision for testing from inspiring English sources

The decision for testing these patients was based on high eosinophil counts, a history of recent travelling to a schistosomiasis endemic region and at least one of the following symptoms: fatigue, gastro-intestinal symptoms, rash or exanthema.

The classification result is weighted average of all of the terminal nodes that are reached, providing the final decision: For testing, the time complexity is O(t · n · m), where n is the number of feature vectors in the testing set, m is the number of features in every feature vector, and t is the number of decision trees considered in the model.

However, whether other factors influenced either the decision for testing or the high rate of positive results was unclear, and the high positive rate may suggest this was a high-risk population at baseline.

Economic models can be valuable for complex decision making and for testing how sensitive a decision is to key estimates or assumptions.

It organizes all binary classifiers into one hierarchical structure (see Figure 1(d)) and makes a decision for test samples from root to leaf, which is helpful for decreasing time complexity of the testing process.

This study was based on actual decisions as the use of hypothetical vignettes often used for testing decision making abilities was not found meaningful.

This has been achieved by dividing the dataset into two parts: one for training the system to imitate real world decision-making and other for testing the system against clinical decisions regarding the diagnosis of meningitis.

When making decisions for testing, clinicians should be aware that many women in Norway, similar to reports from other countries [ 9, 25], acquire their infection from a steady partner, having no obvious risk-factors for gonorrhoea in their medical history.

This was implemented in order to defer design decisions, providing improved opportunities for testing detailed material and fabrication aspects of the project.

Sequential methods are developed for testing multiple hypotheses, resulting in a statistical decision for each individual test and controlling the familywise error rate and the familywise power in the strong sense.

For the outcome stunting, we applied the same decision rule for testing interactions, with one exception.