Sentence examples for survival classifications from inspiring English sources

Median gene centering of the UNC337 dataset before PAM50 or SCMGENE predictions also improved the survival classifications (Supplemental Fig. 1).

A survival Classification and Regression Analysis (CART) algorithm was applied to build the prognostic model for 90-day mortality.

The experimental results showed that gene expression data can be used for valid predictions of cancer patient survival classification with an overall accuracy of 83.0% based on survival time trusted data.

CRSA decision rules for six-month patient survival classification were induced using the MODLEM algorithm.

Receiver operating curve analysis was used to determine the best cut-off value for survival classification.

In this paper, two methods of analysis were considered: a semi-parametric cure regression (Cox cure regression) and a tree-based method, known as survival CART (Classification And Regression Trees) [ 6].

Cox regression analysis revealed that T classification, distant metastasis, and intratumoral or peritumoral CD68+ TAMs were independent factors for disease-free survival, whereas T classification and intratumoral CD68+ TAMs were independent factors for overall survival.

In summary, sub-groups defined by latent class cluster analysis show statistically significant differences in survival and the classification system might therefore be used to stratify patients in clinical trials, and to generate more homogeneous groups for genetic, proteomic and other risk factor research.

We also selected two classes of survival datasets for classification.

In contrast, other studies have failed to identify a correlation between survival and WHO classification [ 14- 16].

The time of onset of weight loss correlated with survival, effectively enabling classification of mutants into two groups.