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Secondary: The utility of other measures for prediction of SDB.
Decision curve analysis can be easily extended to many of the applications common to performance measures for prediction models.
It is our belief that cross-disciplinary research is likely to increase our understanding of all of the dimensions of RVF and thereby, inform the design of comprehensive and cost-effective measures for prediction, detection, and response to RVF.
This analysis represents a secondary analysis from this cohort, which was assembled for a primary analysis of comparing one-dimensional and multi-dimensional psychological measures for prediction of non-recovery related clinical outcomes [ 10].
In this paper, we suggest ways in which information from PET amyloid imaging can be used in combination with cognitive change to improve the utility of these measures for prediction of cognitive decline and impairment and to identify factors that promote cognitive resilience in the presence of Aβ pathology.
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It is defined in Eq. 4. SA is a standardized accuracy measure for prediction techniques (P i ) based on MAR.
It is intuitive that proportion of co-authors of i who have also co-authored j is a good measure for prediction of future co-authorship.
The performance of the different evidence measures was evaluated first to determine their general suitability as a measure for prediction.
The most commonly used surrogate measure for prediction of body fat percentage (BF%) is Body Mass Index (BMI) [ 5- 8].
Thus, the ideal measure for prediction and comparison of growth should be highly correlated with weight and uncorrelated with height [ 11].
No tool is currently available to combine all these putative prognostic predictors into a summary measure for prediction of individual patient outcome.
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assessment for prediction
procedure for prediction
measures for length
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measures for youth
measures for city
measures for utility
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measures for tomorrow
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