Sentence examples for models predicting cancer from inspiring English sources

We then ran multivariable logistic regression models predicting cancer screening for each sample by low health literacy with LEP including control variables (US nativity, age, sex, marital status, insurance, education, living in a rural area, poverty and recent doctor visit).

In the model predicting cancer or death, age and albumin were also retained (Additional file 1).

For unaffected individuals the model predicts cancer risk from a weighted average of the penetrance for mutation carriers and non-carriers, with the estimated carrier probabilities as weights.

In clinical researches, the microarray-based gene expression profiling is often used to construct the models for predicting cancer prognosis.

Our model had significantly higher accuracy than the base model in predicting cancer (area-under-the-curve [AUC] improved from 0.63 to 0.78) or high-grade cancer (AUC increased from 0.77 to 0.87).

The measure of allelic loss of heterozygosity combined with tumor number, tumor size, vascular invasion, lobar distribution, and patient gender provide a highly discriminatory model for predicting cancer recurrence after liver transplantation.

Their approach has provided a useful model for predicting cancer aggressiveness through reliable biomarkers, regardless of sample variation [ 14].

We have integrated several proteomic data sources to develop a model for predicting cancer protein-cancer protein interactions on a global scale based on domain-domain interactions, weighted domain frequency score, and cancer linker degree.

Using the validation sample, unconditional logistic regression models [ 14] predicting cancer status as determined by the algorithm were generated, first among those with OP cancer (for sensitivity) and then among the controls (for specificity).

Table 4 presents the rate ratios obtained from the Poisson regression models predicting breast cancer risk associated with residential proximity to agricultural pesticide use.

We hope that the model presented here will prove complementary to similar models predicting breast cancer mortality in the sense that together they might provide a complete picture of the risk, first of disease progression and then ultimately of death.