Predicting three-year risk of incident colorectal precancerous conditions using non-invasive predictors and machine-learning algorithms: A multi-center retrospective study

Figure 2 Model feature selection. A: Least absolute shrinkage and selection operator procedure for selecting predictors in the training cohort; B: Spearman correlations between included predictors in the training cohort; C: Distribution of selected predictors in participants with and without incident advanced adenoma in the training and validation cohorts (data are medians with interquartile ranges or n (%)). ^aP < 0.05. AA: Advanced adenoma; CA19-9: Carbohydrate antigen 19-9; CYFRA21-1: Cytokeratin 19 fragment; DBP: Diastolic blood pressure; FIT: Fecal immunochemical test; STK1p: Serum thymidine kinase 1 protein.