Sentence examples for better predictive accuracy of from inspiring English sources

Because of this increased risk for CHD, models derived from diabetic populations are expected to offer better predictive accuracy of CHD morbidity and mortality in individuals with diabetes than general population based models.

Using data from the Sweden section of the ERSPC (n = 740), Vickers et al. [ 54] reported that a panel of four kallikrein markers showed significantly better predictive accuracy of biopsy outcome in previously unscreened men with elevated PSA compared with PSA alone (AUC from 0.68 to 0.83, P < 0.0005, and from 0.72 to 0.84, P < 0.0005, without DRE and with DRE, resp).

The network-based markers displayed better predictive accuracy on an independent dataset than markers selected without network information.

de Nazelle et al. (2010) also found better predictive accuracy for the representation of space-time O3 distribution in North Carolina with a BME model based on observed (hard) and modeled (soft) data from a stochastic analysis of an urban-intercontinental-scale atmospheric chemistry transport model, compared with kriging method estimates based on hard data only.

Those scales that included cognition (Ávila-Funes, Rothman and FI) had a better predictive accuracy for all outcomes bar institutionalisation. Strengths of this study include a large sample size, with detailed individual health and service outcomes collated from two sites.

Comparing suPAR with single, routinely used clinical biomarkers of organ dysfunction and inflammation, suPAR displayed better predictive accuracy for both ICU and overall survival in critically ill patients.

We found that the combination of EEG-R and sleep spindles, termed EEG-awakening, presented better predictive accuracy for behavioral awakening than if either was used individually.

We suggest that CHADS2 score provides better predictive accuracy for ischemic stroke in prostate cancer patients.

HAS-BLED demonstrates good predictive accuracy overall, with a better predictive accuracy for patients receiving either no antithrombotic therapy or antiplatelet therapy [ 51].

Fitting a survival model with clinical characteristics in conjunction with SF-12 data achieved better predictive accuracy and goodness-of-fit (C-statistic: 0.956; AIC: 111.2; BIC: 179.8) than models with FACT-C (C-statistic: 0.824; AIC: 128.2; BIC: 187.3) or SF-6D scores (C-statistic: 0.799; AIC: 131.4; BIC: 179.1).

The results indicate that district-level SPFs with county-level adjustment factors provide better predictive accuracy than the development of a statewide SPF or application of the HSM-calibrated SPF.