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2 orithm improves class discrimination and indicates that 113 variables including size, electronegativity, number of valenc

6 epwise Cox regression and the Kaplan-Meier method to assess variables obtained at baseline and at first follow-up RHC.

7 More interestingly, a change of coupling between both variables is observed during deep hypothermic CPB in all subj

9 The scoring system consisted of clinical variables (male sex and previous percutaneous coronary interv

11 The effect was independent of potential confounding variables, including maternal socioeconomic status, obstetric

12 [LDL-C], total cholesterol [TC]) were studied as continuous variables, and results are reported per SD increase of each l

13 l analysis included a 2-sample t test to compare continuous variables, chi-square testing for categorical comparisons, an

14 regression controlling for injury severity and demographic variables, the difference in LOS for Medicaid vs non-Medicaid

15 Data elements were extracted and narratively described variables synthesised into four categories.

16 suggest that the variation and complexity of climate-driven variables could be important for understanding the potential

20 ogy (EFO) is an application ontology driven by experimental variables including cell lines to organize and describe the d

21 ell lines to organize and describe the diverse experimental variables and data resided in the EMBL-EBI resources.

23 m" must be examined carefully along with other experimental variables, keeping in mind that the effects of EVs may be acc

27 andomization is the use of genetic variants as instrumental variables to estimate causal effects of risk factors on outco

30 ely age, sex, and ethnicity; however, several patient-level variables could not be included in our analysis because of hi

31 ute respiratory distress syndrome onset, neither mechanical variables nor PaO2/FIO2 were associated with mortality.

33 re chemically analysed and employed to reduce the number of variables used to construct the models.

34 known to reflect a range of psychological and physiological variables, including cognitive effort, arousal, attention, an

35 A clinical tool using readily available pretest variables discriminates such minimal-risk patients, for whom

37 on, which uses repeated internal cross-validation to select variables and estimate coefficients in the presence of collin

38 In regression analyses, models comprising significant variables, but not the variables themselves, predicted involv

41 lyses, models comprising significant variables, but not the variables themselves, predicted involvement/non-involvement i

47 ty risk was explained by multivariable modelling with these variables; however, the remainder was unexplained.

49 tical depth (AOD) data, meteorological fields, and land use variables to estimate daily 24 h averaged ground-level PM2.5

50 We used survey design and weighting variables to produce national estimates of annual adult emerg

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