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We determined accuracy of the predictions by computing the Pearson correlation between the predicted and the measured score improvement for all 34 subjects.
The overall ability of models to correctly identify results was then determined (accuracy).
The performance measures were determined (accuracy and Cohen's kappa) for each of the steps, and the mean values were calculated.
We determined accuracy of specific codes and coding algorithm by calculating PPV with 95% confidence intervals (CI).
Studies that determined accuracy (eg, positive-predictive value) of family breast cancer history, 25– 29 expanded first-degree relatives to include aunts, 30 did not distinguish between FDRs and second-degree relatives, 31 validated bilateral breast cancer, 32 or were a sub-study of a larger included validation study 33 were not used.
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Ergo, accurately determining accuracy is another (bot-spotting related) problem.
The investigators then reviewed the interpretations to determine accuracy.
The numerical parameters that determine accuracy are investigated.
To determine accuracy, sensor values were compared to the simultaneously recorded blood glucose values from PDMS.
A theoretical and experimental error analysis is done to determine accuracy and robustness of the measurements.
Absolute error quartiles and percentage of trials in absolute error threshold ranges were used to determine accuracy.
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