Sentence examples for median relative deviation from inspiring English sources

Algorithm performance was assessed by smoothing the simulated data using a given model and calculating the median relative deviation of observations from the fit for each timepoint in each experiment.

The development of a framework for stochastic generation of extracellular compound concentration trends was based on the need to estimate the variability of median relative deviations from a smoothing fit.

Since increasing and decreasing trends reach their minimum concentrations at different endpoints, the overall effect on median relative deviations is not pronounced when the two trends are balanced in number.

Sensor performance was good, with the median absolute deviation of 0.5 (0.3 to 1.0) m M, median relative absolute deviation of 7.0% (3.5 to 13.0), with 87.8% of sensor values within 20% of reference glucose.

A quality control value assessment was undertaken to determine instrument variability by calculating the median relative standard deviation (RSD) for the internal standards that were pre-mixed into each sample prior to injection into the mass spectrometer.

Parsons et al. have proposed using median relative standard deviation as a practical benchmark [33].

The median relative standard deviation (MRSD), a quality assurance metric of quantification and measure of instrument variability, was determined to be 8% for a panel of 30 internal standards.

Comparison of platforms was based on average metabolite missingness level across samples and the median relative standard deviation (RSD) across biological replicates.

The accuracy of the CGM and the POC device was assessed by calculating the median relative absolute deviation (RAD) between reference glucose and CGM or POC glucose.

Instrument variability was determined by calculating the median relative standard deviation (RSD) for internal standards that were added to each sample prior to injection into the mass spectrometers.

CGM accuracy during 3-month home phase against capillary glucose measurements will be evaluated using standard measures of numerical and clinical accuracy including mean and median absolute relative deviation, bias, International Standardization Organization criteria and Clarke error grid analysis.