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For comparative purposes, we compared the predictive performance of the above methods with previously developed disease-specific mortality prediction models.
Furthermore, we compared the predictive performance of the ANN model to the prediction of logistic regression model.
To assess the potential to predict BPD or death, we compared the predictive value of SNAP with other prognostic predictors demonstrated by multivariate regression analysis (Table 3).
In addition we compared the predictive power of these cut-off points in predicting mortality in Cox Regression models.
We also compared the predictive powers of individual and combined characteristics in making better predictions.
Several studies have compared the predictive value of MetS with that of the Framingham risk prediction model.
It compared the predictive validity of three numbers: a student's high-school G.P.A., his or her score on the S.A.T. (or, as it is formally known, the S.A.T. I), and his or her score on what is known as the S.A.T. II, which is a so-called achievement test, aimed at gauging mastery of specific areas of the high-school curriculum.
We also compared the predictive performance of two vegetation layers differing in their floristic detail and spatial accuracy.
As shown in Fig. 5, it compared the predictive classification results of the composition models and direct models at three localities.
However, with respect to clinical use for various adverse outcomes, no known study has compared the predictive performance of these indices specifically following posterior lumbar fusion (PLF).
The study compared the predictive value of admission plasma glucose (APG) and first fasting plasma glucose (FPG) in stratifying patients meriting an oral glucose tolerance test (OGTT).
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