Sentence examples for data familiarity from inspiring English sources

In the absence of long-term safety data, familiarity with short-term use and its apparent safety profile led to the introduction of etomidate as a continuous infusion for ICU sedation, with resulting adverse events including adrenal suppression and a 19% absolute increase in mortality in trauma patients [ 19, 20].

Data on familiarity with, and perceptions of similarity among 11 engineering specialties were collected from 129 undergraduate engineering students from a public urban university.

We examine how the design features underlying these ethical issues are characteristic of effectiveness trials, which are often large trials that compare treatments with varying degrees of existing effectiveness data and familiarity to patients and clinicians, in community-based treatment settings, with minimal exclusion criteria that could involve vulnerable populations.

The researcher (MR) spent time in the clinic area gathering data, developing familiarity with the context and the environment.

Such ignorance may be due to a lack of data or familiarity with the problem at hand, imprecision in assessment, or the absence of certain stakeholders in a group decision (Durbach and Stewart, 2012).

Of note is that data on familiarity can be identified from the features of the physical environment, in that several falls occurred near to home (11/76 comments), or in the garden (4/76 comments), with only one outdoor fall experienced while on holiday.

The familiarity data were collected under NIH grant R01 LM007222-05 (PI: Qing Zeng-Treitler) and the numeracy data were collected as part of AHRQ R03-HS016333 (PI: Rita Kukafka).

Furthermore, statistical t-test revealed that classifying PSD features with either SVM or MLP using data from low familiarity music video sessions were significantly better than classifying by the same approach using the overall dataset.

In arousal recognition, the best result over the chance level was obtained by classifying PSD features with SVM using data from low familiarity sessions; this methodology achieved 73.30 % ((SD = 7.71, %)) averaged accuracy across subjects against a chance level of 64.15 % ((SD = 10.70, %)).

For each of the 64 pictures, normative data for concept familiarity, age of acquisition, name agreement and visual complexity were available.

We will use framework methodology to aid data management, gain familiarity with the data and identify themes and categories to explore further.