for locally advanced gastric or gastroesophageal junction (G/GEJ) cancer: Asia versus non-Asia subgroup analysis of KEYNOTE-585. Univariable and multivariable logistic regression for association of ...

Receiver operating characteristic (ROC) curves were generated from the final multivariable logistic regression models ... receiver operating characteristic. Table 1 Specificity, Positive and Negative ...

A multivariable logistic regression model was constructed for defining the important ... All analyses were performed with the use of SAS software version 9.2 (SAS Institute, NC). Table 1 shows the ...

These variables were integrated into an initial model, and a multivariable ... main diagonal of Table 5 and divide them by the sample considered by the ANN, we see that the accuracy is approximately ...

ReliefF feature selection coupled with an L2-regularized logistic regression based classifier was ... in the top-ranked lipid analytes used in the multivariate models. Abbreviations are as defined in ...

A multivariate logistic regression model was constructed for analysis, and the results are presented in Table 4. Based on the significant characteristic factors identified in the logistic regression ...

The study developed novel indices (RAR, NPAR, SIRI, Homair) and assessed their CKM predictive value through: Multivariable logistic ... weighted for representativeness. Table 3. Multimodal logistic ...

Statistically significant covariates (α=5%) in univariate analyses were included in a stepwise logistic regression ... moderate disease course Table 5 indicates the variables selected by univariate ...

The only factor significantly associated with the use of ECPR in multivariate logistic regression analysis was age (OR=0.07; 95% CI 0.01 to 0.85; p=0.037). All factors are displayed in table 2. This ...

Rigorous study design and analytical standards are required to generate reliable findings in healthcare from artificial intelligence (AI) research. One crucial but often overlooked aspect is the ...