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

Figure 4 Model interpretation and application. A: Scatter plots showing the relationship of actual values of included predictors with SHapley Additive exPlanations (SHAP) values and a second predictor with the strongest correlation; B: Feature importance ranked by mean absolute SHAP values; C: SHAP beeswarm plots illustrating impact distributions of included predictors; D: Online EXtreme Gradient Boosting prediction tool accessible at https://precrc.shinyapps.io/precrc/. A predicted probability ≥ 50% and < 50% is coded as 1 and 0, respectively; E: Percentage of incident advanced adenoma in EXtreme Gradient Boosting predicted high-risk and low-risk groups (0 = low risk, 1 = high risk). CA19-9: Carbohydrate antigen 19-9; CYFRA21-1: Cytokeratin 19 fragment; DBP: Diastolic blood pressure; FIT: Fecal immunochemical test; SHAP: SHapley Additive exPlanations; STK1p: Serum thymidine kinase 1 protein; XGBOOST: EXtreme Gradient Boosting.